class ALOS2(Sensor): """ Code to read CEOSFormat leader files for ALOS2 SLC data. """ family = 'alos2' parameter_list = (WAVELENGTH, LEADERFILE, IMAGEFILE) + Sensor.parameter_list fsampConst = { 104: 1.047915957140240E+08, 52: 5.239579785701190E+07, 34: 3.493053190467460E+07, 17: 1.746526595233730E+07 } #Orbital Elements (Quality) Designator #ALOS-2/PALSAR-2 Level 1.1/1.5/2.1/3.1 CEOS SAR Product Format Description #PALSAR-2_xx_Format_CEOS_E_r.pdf orbitElementsDesignator = { '0': 'preliminary', '1': 'decision', '2': 'high precision' } def __init__(self, name=''): super().__init__(family=self.__class__.family, name=name) self.leaderFile = None self.imageFile = None #####Soecific doppler functions for ALOS2 self.doppler_coeff = None self.azfmrate_coeff = None self.lineDirection = None self.pixelDirection = None self.frame = Frame() self.frame.configure() self.constants = {'polarization': 'HH', 'antennaLength': 10} def getFrame(self): return self.frame def parse(self): self.leaderFile = LeaderFile(self, file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(self, file=self._imageFile) self.imageFile.parse() self.populateMetadata() def populateMetadata(self): """ Create the appropriate metadata objects from our CEOSFormat metadata """ frame = self._decodeSceneReferenceNumber( self.leaderFile.sceneHeaderRecord. metadata['Scene reference number']) fsamplookup = int(self.leaderFile.sceneHeaderRecord. metadata['Range sampling rate in MHz']) rangePixelSize = Const.c / (2 * self.fsampConst[fsamplookup]) ins = self.frame.getInstrument() platform = ins.getPlatform() platform.setMission(self.leaderFile.sceneHeaderRecord. metadata['Sensor platform mission identifier']) platform.setAntennaLength(self.constants['antennaLength']) platform.setPointingDirection(1) platform.setPlanet(Planet(pname='Earth')) if self.wavelength: ins.setRadarWavelength(float(self.wavelength)) # print('ins.radarWavelength = ', ins.getRadarWavelength(), # type(ins.getRadarWavelength())) else: ins.setRadarWavelength( self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength']) ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord. metadata['Incidence angle at scene centre']) self.frame.getInstrument().setPulseRepetitionFrequency( self.leaderFile.sceneHeaderRecord. metadata['Pulse Repetition Frequency in mHz'] * 1.0e-3) ins.setRangePixelSize(rangePixelSize) ins.setRangeSamplingRate(self.fsampConst[fsamplookup]) ins.setPulseLength(self.leaderFile.sceneHeaderRecord. metadata['Range pulse length in microsec'] * 1.0e-6) chirpSlope = self.leaderFile.sceneHeaderRecord.metadata[ 'Nominal range pulse (chirp) amplitude coefficient linear term'] chirpPulseBandwidth = abs( chirpSlope * self.leaderFile.sceneHeaderRecord. metadata['Range pulse length in microsec'] * 1.0e-6) ins.setChirpSlope(chirpSlope) ins.setInPhaseValue(7.5) ins.setQuadratureValue(7.5) self.lineDirection = self.leaderFile.sceneHeaderRecord.metadata[ 'Time direction indicator along line direction'].strip() self.pixelDirection = self.leaderFile.sceneHeaderRecord.metadata[ 'Time direction indicator along pixel direction'].strip() ######ALOS2 includes this information in clock angle clockAngle = self.leaderFile.sceneHeaderRecord.metadata[ 'Sensor clock angle'] if clockAngle == 90.0: platform.setPointingDirection(-1) elif clockAngle == -90.0: platform.setPointingDirection(1) else: raise Exception( 'Unknown look side. Clock Angle = {0}'.format(clockAngle)) # print(self.leaderFile.sceneHeaderRecord.metadata["Sensor ID and mode of operation for this channel"]) self.frame.setFrameNumber(frame) self.frame.setOrbitNumber( self.leaderFile.sceneHeaderRecord.metadata['Orbit number']) self.frame.setProcessingFacility( self.leaderFile.sceneHeaderRecord. metadata['Processing facility identifier']) self.frame.setProcessingSystem( self.leaderFile.sceneHeaderRecord. metadata['Processing system identifier']) self.frame.setProcessingSoftwareVersion( self.leaderFile.sceneHeaderRecord. metadata['Processing version identifier']) self.frame.setPolarization(self.constants['polarization']) self.frame.setNumberOfLines( self.imageFile.imageFDR.metadata['Number of lines per data set']) self.frame.setNumberOfSamples( self.imageFile.imageFDR. metadata['Number of pixels per line per SAR channel']) ###### orb = self.frame.getOrbit() orb.setOrbitSource('Header') orb.setOrbitQuality(self.orbitElementsDesignator[ self.leaderFile.platformPositionRecord. metadata['Orbital elements designator']]) t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord. metadata['Year of data point'], month=self.leaderFile.platformPositionRecord. metadata['Month of data point'], day=self.leaderFile.platformPositionRecord. metadata['Day of data point']) t0 = t0 + datetime.timedelta( seconds=self.leaderFile.platformPositionRecord. metadata['Seconds of day']) #####Read in orbit in inertial coordinates deltaT = self.leaderFile.platformPositionRecord.metadata[ 'Time interval between data points'] numPts = self.leaderFile.platformPositionRecord.metadata[ 'Number of data points'] orb = self.frame.getOrbit() for i in range(numPts): vec = StateVector() t = t0 + datetime.timedelta(seconds=i * deltaT) vec.setTime(t) dataPoints = self.leaderFile.platformPositionRecord.metadata[ 'Positional Data Points'][i] pos = [ dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z'] ] vel = [ dataPoints['Velocity vector X'], dataPoints['Velocity vector Y'], dataPoints['Velocity vector Z'] ] vec.setPosition(pos) vec.setVelocity(vel) orb.addStateVector(vec) self.doppler_coeff = [ self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency centroid constant term'], self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency centroid linear term'], self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency centroid quadratic term'] ] self.azfmrate_coeff = [ self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency rate constant term'], self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency rate linear term'], self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency rate quadratic term'] ] # print('Terrain height: ', self.leaderFile.sceneHeaderRecord.metadata['Average terrain ellipsoid height']) def extractImage(self): import isceobj if (self.imageFile is None) or (self.leaderFile is None): self.parse() try: out = open(self.output, 'wb') except IOError as strerr: self.logger.error("IOError: %s" % strerr) self.imageFile.extractImage(output=out) out.close() # rangeGate = self.leaderFile.sceneHeaderRecord.metadata['Range gate delay in microsec']*1e-6 # delt = datetime.timedelta(seconds=rangeGate) delt = datetime.timedelta(seconds=0.0) self.frame.setSensingStart(self.imageFile.sensingStart + delt) self.frame.setSensingStop(self.imageFile.sensingStop + delt) sensingMid = self.imageFile.sensingStart + datetime.timedelta( seconds=0.5 * (self.imageFile.sensingStop - self.imageFile.sensingStart).total_seconds()) + delt self.frame.setSensingMid(sensingMid) self.frame.setStartingRange(self.imageFile.nearRange) self.frame.getInstrument().setPulseRepetitionFrequency( self.imageFile.prf) pixelSize = self.frame.getInstrument().getRangePixelSize() farRange = self.imageFile.nearRange + (pixelSize - 1) * self.imageFile.width self.frame.setFarRange(farRange) rawImage = isceobj.createSlcImage() rawImage.setByteOrder('l') rawImage.setAccessMode('read') rawImage.setFilename(self.output) rawImage.setWidth(self.imageFile.width) rawImage.setXmin(0) rawImage.setXmax(self.imageFile.width) rawImage.renderHdr() self.frame.setImage(rawImage) return def extractDoppler(self): ''' Evaluate the doppler polynomial and return the average value for now. ''' midwidth = self.frame.getNumberOfSamples() / 2.0 dop = 0.0 prod = 1.0 for ind, kk in enumerate(self.doppler_coeff): dop += kk * prod prod *= midwidth print('Average Doppler: {0}'.format(dop)) ####For insarApp quadratic = {} quadratic['a'] = dop / self.frame.getInstrument( ).getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. ####For roiApp ####More accurate ####CEOS already provides function vs pixel self.frame._dopplerVsPixel = self.doppler_coeff return quadratic def _decodeSceneReferenceNumber(self, referenceNumber): return referenceNumber
class EnviSAT_SLC(Sensor): parameter_list = (ORBIT_DIRECTORY, ORBITFILE, INSTRUMENTFILE, INSTRUMENT_DIRECTORY, IMAGEFILE) + Sensor.parameter_list """ A Class for parsing EnviSAT instrument and imagery files """ family = 'envisat' def __init__(self, family='', name=''): super(EnviSAT_SLC, self).__init__(family if family else self.__class__.family, name=name) self._imageFile = None self._instrumentFileData = None self._imageryFileData = None self.dopplerRangeTime = None self.rangeRefTime = None self.logger = logging.getLogger("isce.sensor.EnviSAT_SLC") self.frame = None self.frameList = [] self.constants = {'antennaLength': 10.0, 'iBias': 128, 'qBias': 128} def getFrame(self): return self.frame def parse(self): """ Parse both imagery and instrument files and create objects representing the platform, instrument and scene """ self.frame = Frame() self.frame.configure() self._imageFile = ImageryFile(fileName=self._imageFileName) self._imageryFileData = self._imageFile.parse() if self.instrumentFile in [None, '']: self.findInstrumentFile() instrumentFileParser = InstrumentFile(fileName=self.instrumentFile) self._instrumentFileData = instrumentFileParser.parse() self.populateMetadata() def populateMetadata(self): self._populatePlatform() self._populateInstrument() self._populateFrame() self._populateOrbit() self.dopplerRangeTime = self._imageryFileData['doppler'] self.rangeRefTime = self._imageryFileData['dopplerOrigin'][0] * 1.0e-9 # print('Doppler confidence: ', 100.0 * self._imageryFileData['dopplerConfidence'][0]) def _populatePlatform(self): """Populate the platform object with metadata""" platform = self.frame.getInstrument().getPlatform() # Populate the Platform and Scene objects platform.setMission("Envisat") platform.setPointingDirection(-1) platform.setAntennaLength(self.constants['antennaLength']) platform.setPlanet(Planet(pname="Earth")) def _populateInstrument(self): """Populate the instrument object with metadata""" instrument = self.frame.getInstrument() rangeSampleSpacing = Const.c / ( 2 * self._imageryFileData['rangeSamplingRate']) pri = self._imageryFileData['pri'] ####These shouldnt matter for SLC data since data is already focused. txPulseLength = 512 / 19207680.000000 chirpPulseBandwidth = 16.0e6 chirpSlope = chirpPulseBandwidth / txPulseLength instrument.setRangePixelSize(rangeSampleSpacing) instrument.setPulseLength(txPulseLength) #instrument.setSwath(imageryFileData['SWATH']) instrument.setRadarFrequency(self._instrumentFileData['frequency']) instrument.setChirpSlope(chirpSlope) instrument.setRangeSamplingRate( self._imageryFileData['rangeSamplingRate']) instrument.setPulseRepetitionFrequency(1.0 / pri) #instrument.setRangeBias(rangeBias) instrument.setInPhaseValue(self.constants['iBias']) instrument.setQuadratureValue(self.constants['qBias']) def _populateFrame(self): """Populate the scene object with metadata""" numberOfLines = self._imageryFileData['numLines'] numberOfSamples = self._imageryFileData['numSamples'] pri = self._imageryFileData['pri'] startingRange = Const.c * float( self._imageryFileData['timeToFirstSample']) * 1.0e-9 / 2.0 rangeSampleSpacing = Const.c / ( 2 * self._imageryFileData['rangeSamplingRate']) farRange = startingRange + numberOfSamples * rangeSampleSpacing first_line_utc = datetime.datetime.strptime( self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f') center_line_utc = datetime.datetime.strptime( self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f') last_line_utc = datetime.datetime.strptime( self._imageryFileData['LAST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f') centerTime = DTUtil.timeDeltaToSeconds(last_line_utc - first_line_utc) / 2.0 center_line_utc = center_line_utc + datetime.timedelta( microseconds=int(centerTime * 1e6)) self.frame.setStartingRange(startingRange) self.frame.setFarRange(farRange) self.frame.setProcessingFacility(self._imageryFileData['PROC_CENTER']) self.frame.setProcessingSystem(self._imageryFileData['SOFTWARE_VER']) self.frame.setTrackNumber(int(self._imageryFileData['REL_ORBIT'])) self.frame.setOrbitNumber(int(self._imageryFileData['ABS_ORBIT'])) self.frame.setPolarization(self._imageryFileData['MDS1_TX_RX_POLAR']) self.frame.setNumberOfSamples(numberOfSamples) self.frame.setNumberOfLines(numberOfLines) self.frame.setSensingStart(first_line_utc) self.frame.setSensingMid(center_line_utc) self.frame.setSensingStop(last_line_utc) def _populateOrbit(self): if self.orbitFile in [None, '']: self.findOrbitFile() dorParser = DOR(fileName=self.orbitFile) dorParser.parse() startTime = self.frame.getSensingStart() - datetime.timedelta( minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.frame.setOrbit(dorParser.orbit.trimOrbit(startTime, stopTime)) def _populateImage(self, outname, width, length): #farRange = self.frame.getStartingRange() + width*self.frame.getInstrument().getRangeSamplingRate() # Update the NumberOfSamples and NumberOfLines in the Frame object self.frame.setNumberOfSamples(width) self.frame.setNumberOfLines(length) #self.frame.setFarRange(farRange) # Create a RawImage object rawImage = createSlcImage() rawImage.setFilename(outname) rawImage.setAccessMode('read') rawImage.setByteOrder('l') rawImage.setXmin(0) rawImage.setXmax(width) rawImage.setWidth(width) self.frame.setImage(rawImage) def extractImage(self): from datetime import datetime as dt import tempfile as tf self.parse() width = self._imageryFileData['numSamples'] length = self._imageryFileData['numLines'] self._imageFile.extractImage(self.output, width, length) self._populateImage(self.output, width, length) pass def findOrbitFile(self): datefmt = '%Y%m%d%H%M%S' # sensingStart = self.frame.getSensingStart() sensingStart = datetime.datetime.strptime( self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f') outFile = None if self.orbitDir in [None, '']: raise Exception( 'No Envisat Orbit File or Orbit Directory specified') try: for fname in os.listdir(self.orbitDir): if not os.path.isfile(os.path.join(self.orbitDir, fname)): continue if not fname.startswith('DOR'): continue fields = fname.split('_') procdate = datetime.datetime.strptime( fields[-6][-8:] + fields[-5], datefmt) startdate = datetime.datetime.strptime(fields[-4] + fields[-3], datefmt) enddate = datetime.datetime.strptime(fields[-2] + fields[-1], datefmt) if (sensingStart > startdate) and (sensingStart < enddate): outFile = os.path.join(self.orbitDir, fname) break except: raise Exception( 'Error occured when trying to find orbit file in %s' % (self.orbitDir)) if not outFile: raise Exception('Envisat orbit file could not be found in %s' % (self.orbitDir)) self.orbitFile = outFile return def findInstrumentFile(self): datefmt = '%Y%m%d%H%M%S' sensingStart = datetime.datetime.strptime( self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f') print('sens: ', sensingStart) outFile = None if self.instrumentDir in [None, '']: raise Exception( 'No Envisat Instrument File or Instrument Directory specified') try: for fname in os.listdir(self.instrumentDir): if not os.path.isfile(os.path.join(self.instrumentDir, fname)): continue if not fname.startswith('ASA_INS'): continue fields = fname.split('_') procdate = datetime.datetime.strptime( fields[-6][-8:] + fields[-5], datefmt) startdate = datetime.datetime.strptime(fields[-4] + fields[-3], datefmt) enddate = datetime.datetime.strptime(fields[-2] + fields[-1], datefmt) if (sensingStart > startdate) and (sensingStart < enddate): outFile = os.path.join(self.instrumentDir, fname) break except: raise Exception( 'Error occured when trying to find instrument file in %s' % (self.instrumentDir)) if not outFile: raise Exception( 'Envisat instrument file could not be found in %s' % (self.instrumentDir)) self.instrumentFile = outFile return def extractDoppler(self): """ Return the doppler centroid as defined in the ASAR file. """ quadratic = {} r0 = self.frame.getStartingRange() dr = self.frame.instrument.getRangePixelSize() width = self.frame.getNumberOfSamples() midr = r0 + (width / 2.0) * dr midtime = 2 * midr / Const.c - self.rangeRefTime fd_mid = 0.0 tpow = midtime for kk in self.dopplerRangeTime: fd_mid += kk * tpow tpow *= midtime ####For insarApp quadratic['a'] = fd_mid / self.frame.getInstrument( ).getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. ####For roiApp ####More accurate from isceobj.Util import Poly1D coeffs = self.dopplerRangeTime dr = self.frame.getInstrument().getRangePixelSize() rref = 0.5 * Const.c * self.rangeRefTime r0 = self.frame.getStartingRange() norm = 0.5 * Const.c / dr dcoeffs = [] for ind, val in enumerate(coeffs): dcoeffs.append(val / (norm**ind)) poly = Poly1D.Poly1D() poly.initPoly(order=len(coeffs) - 1) poly.setMean((rref - r0) / dr - 1.0) poly.setCoeffs(dcoeffs) pix = np.linspace(0, self.frame.getNumberOfSamples(), num=len(coeffs) + 1) evals = poly(pix) fit = np.polyfit(pix, evals, len(coeffs) - 1) self.frame._dopplerVsPixel = list(fit[::-1]) print('Doppler Fit: ', fit[::-1]) return quadratic
class KOMPSAT5(Component): """ A class representing a Level1Product meta data. Level1Product(hdf5=h5filename) will parse the hdf5 file and produce an object with attributes for metadata. """ logging_name = 'isce.Sensor.KOMPSAT5' def __init__(self): super(KOMPSAT5,self).__init__() self.hdf5 = None self.output = None self.frame = Frame() self.frame.configure() # Some extra processing parameters unique to CSK SLC (currently) self.dopplerCoeffs = [] self.rangeFirstTime = None self.rangeLastTime = None self.rangeRefTime = None self.refUTC = None self.descriptionOfVariables = {} self.dictionaryOfVariables = {'HDF5': ['self.hdf5','str','mandatory'], 'OUTPUT': ['self.output','str','optional']} self.lookMap = {'RIGHT': -1, 'LEFT': 1} return def __getstate__(self): d = dict(self.__dict__) del d['logger'] return d def __setstate__(self,d): self.__dict__.update(d) self.logger = logging.getLogger('isce.Sensor.COSMO_SkyMed_SLC') return def getFrame(self): return self.frame def parse(self): try: fp = h5py.File(self.hdf5,'r') except Exception as strerr: self.logger.error("IOError: %s" % strerr) return None self.populateMetadata(fp) fp.close() def populateMetadata(self, file): """ Populate our Metadata objects """ self._populatePlatform(file) self._populateInstrument(file) self._populateFrame(file) self._populateOrbit(file) self._populateExtras(file) def _populatePlatform(self, file): platform = self.frame.getInstrument().getPlatform() platform.setMission(file.attrs['Satellite ID']) platform.setPointingDirection(self.lookMap[file.attrs['Look Side'].decode('utf-8')]) platform.setPlanet(Planet("Earth")) ####This is an approximation for spotlight mode ####In spotlight mode, antenna length changes with azimuth position platform.setAntennaLength(file.attrs['Antenna Length']) try: if file.attrs['Multi-Beam ID'].startswith('ES'): platform.setAntennaLength(16000.0/file['S01/SBI'].attrs['Line Time Interval']) except: pass def _populateInstrument(self, file): instrument = self.frame.getInstrument() # rangePixelSize = Const.c/(2*file['S01'].attrs['Sampling Rate']) rangePixelSize = file['S01/SBI'].attrs['Column Spacing'] instrument.setRadarWavelength(file.attrs['Radar Wavelength']) # instrument.setPulseRepetitionFrequency(file['S01'].attrs['PRF']) instrument.setPulseRepetitionFrequency(1.0/file['S01/SBI'].attrs['Line Time Interval']) instrument.setRangePixelSize(rangePixelSize) instrument.setPulseLength(file['S01'].attrs['Range Chirp Length']) instrument.setChirpSlope(file['S01'].attrs['Range Chirp Rate']) # instrument.setRangeSamplingRate(file['S01'].attrs['Sampling Rate']) instrument.setRangeSamplingRate(1.0/file['S01/SBI'].attrs['Column Time Interval']) incangle = 0.5*(file['S01/SBI'].attrs['Far Incidence Angle'] + file['S01/SBI'].attrs['Near Incidence Angle']) instrument.setIncidenceAngle(incangle) def _populateFrame(self, file): rft = file['S01/SBI'].attrs['Zero Doppler Range First Time'] slantRange = rft*Const.c/2.0 self.frame.setStartingRange(slantRange) referenceUTC = self._parseNanoSecondTimeStamp(file.attrs['Reference UTC']) relStart = file['S01/SBI'].attrs['Zero Doppler Azimuth First Time'] relEnd = file['S01/SBI'].attrs['Zero Doppler Azimuth Last Time'] relMid = 0.5*(relStart + relEnd) sensingStart = self._combineDateTime(referenceUTC, relStart) sensingStop = self._combineDateTime(referenceUTC, relEnd) sensingMid = self._combineDateTime(referenceUTC, relMid) self.frame.setPassDirection(file.attrs['Orbit Direction']) self.frame.setOrbitNumber(file.attrs['Orbit Number']) self.frame.setProcessingFacility(file.attrs['Processing Centre']) self.frame.setProcessingSoftwareVersion(file.attrs['L0 Software Version']) self.frame.setPolarization(file['S01'].attrs['Polarisation']) self.frame.setNumberOfLines(file['S01/SBI'].shape[0]) self.frame.setNumberOfSamples(file['S01/SBI'].shape[1]) self.frame.setSensingStart(sensingStart) self.frame.setSensingMid(sensingMid) self.frame.setSensingStop(sensingStop) rangePixelSize = self.frame.getInstrument().getRangePixelSize() farRange = slantRange + (self.frame.getNumberOfSamples()-1)*rangePixelSize self.frame.setFarRange(farRange) def _populateOrbit(self,file): orbit = self.frame.getOrbit() orbit.setReferenceFrame('ECR') orbit.setOrbitSource('Header') t0 = datetime.datetime.strptime(file.attrs['Reference UTC'].decode('utf-8'),'%Y-%m-%d %H:%M:%S.%f000') t = file.attrs['State Vectors Times'] position = file.attrs['ECEF Satellite Position'] velocity = file.attrs['ECEF Satellite Velocity'] for i in range(len(position)): vec = StateVector() dt = t0 + datetime.timedelta(seconds=t[i]) vec.setTime(dt) vec.setPosition([position[i,0],position[i,1],position[i,2]]) vec.setVelocity([velocity[i,0],velocity[i,1],velocity[i,2]]) orbit.addStateVector(vec) def _populateExtras(self, file): """ Populate some of the extra fields unique to processing TSX data. In the future, other sensors may need this information as well, and a re-organization may be necessary. """ from isceobj.Doppler.Doppler import Doppler scale = file['S01'].attrs['PRF'] * file['S01/SBI'].attrs['Line Time Interval'] self.dopplerCoeffs = file.attrs['Centroid vs Range Time Polynomial']*scale self.rangeRefTime = file.attrs['Range Polynomial Reference Time'] self.rangeFirstTime = file['S01/SBI'].attrs['Zero Doppler Range First Time'] self.rangeLastTime = file['S01/SBI'].attrs['Zero Doppler Range Last Time'] def extractImage(self): import os from ctypes import cdll, c_char_p extract_csk = cdll.LoadLibrary(os.path.dirname(__file__)+'/csk.so') inFile_c = c_char_p(bytes(self.hdf5, 'utf-8')) outFile_c = c_char_p(bytes(self.output, 'utf-8')) extract_csk.extract_csk_slc(inFile_c, outFile_c) self.parse() slcImage = isceobj.createSlcImage() slcImage.setFilename(self.output) slcImage.setXmin(0) slcImage.setXmax(self.frame.getNumberOfSamples()) slcImage.setWidth(self.frame.getNumberOfSamples()) slcImage.setAccessMode('r') self.frame.setImage(slcImage) def _parseNanoSecondTimeStamp(self,timestamp): """ Parse a date-time string with nanosecond precision and return a datetime object """ dateTime,nanoSeconds = timestamp.decode('utf-8').split('.') microsec = float(nanoSeconds)*1e-3 dt = datetime.datetime.strptime(dateTime,'%Y-%m-%d %H:%M:%S') dt = dt + datetime.timedelta(microseconds=microsec) return dt def _combineDateTime(self,dobj, secsstr): '''Takes the date from dobj and time from secs to spit out a date time object. ''' sec = float(secsstr) dt = datetime.timedelta(seconds = sec) return dobj + dt def extractDoppler(self): """ Return the doppler centroid as defined in the HDF5 file. """ quadratic = {} midtime = (self.rangeLastTime + self.rangeFirstTime)*0.5 - self.rangeRefTime fd_mid = self.dopplerCoeffs[0] + self.dopplerCoeffs[1]*midtime + self.dopplerCoeffs[2]*midtime*midtime quadratic['a'] = fd_mid/self.frame.getInstrument().getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. return quadratic
class Sentinel1A(Component): """ A Class representing RadarSAT 2 data """ def __init__(self): Component.__init__(self) self.xml = None self.tiff = None self.output = None self.gdal_translate = None self.frame = Frame() self.frame.configure() self._xml_root = None self.descriptionOfVariables = {} self.dictionaryOfVariables = { 'XML': ['self.xml', 'str', 'mandatory'], 'TIFF': ['self.tiff', 'str', 'mandatory'], 'OUTPUT': ['self.output', 'str', 'optional'], 'GDAL_TRANSLATE': ['self.gdal_translate', 'str', 'optional'] } def getFrame(self): return self.frame def parse(self): try: fp = open(self.xml, 'r') except IOError as strerr: print("IOError: %s" % strerr) return self._xml_root = ElementTree(file=fp).getroot() # self.product.set_from_etnode(self._xml_root) self.populateMetadata() fp.close() def grab_from_xml(self, path): try: res = self._xml_root.find(path).text except: raise Exception('Tag= %s not found' % (path)) if res is None: raise Exception('Tag = %s not found' % (path)) return res def convertToDateTime(self, string): dt = datetime.datetime.strptime(string, "%Y-%m-%dT%H:%M:%S.%f") return dt def populateMetadata(self): """ Create metadata objects from the metadata files """ ####Set each parameter one - by - one mission = self.grab_from_xml('adsHeader/missionId') swath = self.grab_from_xml('adsHeader/swath') polarization = self.grab_from_xml('adsHeader/polarisation') frequency = float( self.grab_from_xml( 'generalAnnotation/productInformation/radarFrequency')) passDirection = self.grab_from_xml( 'generalAnnotation/productInformation/pass') rangePixelSize = float( self.grab_from_xml( 'imageAnnotation/imageInformation/rangePixelSpacing')) azimuthPixelSize = float( self.grab_from_xml( 'imageAnnotation/imageInformation/azimuthPixelSpacing')) rangeSamplingRate = Const.c / (2.0 * rangePixelSize) prf = 1.0 / float( self.grab_from_xml( 'imageAnnotation/imageInformation/azimuthTimeInterval')) lines = int( self.grab_from_xml( 'imageAnnotation/imageInformation/numberOfLines')) samples = int( self.grab_from_xml( 'imageAnnotation/imageInformation/numberOfSamples')) startingRange = float( self.grab_from_xml( 'imageAnnotation/imageInformation/slantRangeTime') ) * Const.c / 2.0 incidenceAngle = float( self.grab_from_xml( 'imageAnnotation/imageInformation/incidenceAngleMidSwath')) dataStartTime = self.convertToDateTime( self.grab_from_xml( 'imageAnnotation/imageInformation/productFirstLineUtcTime')) dataStopTime = self.convertToDateTime( self.grab_from_xml( 'imageAnnotation/imageInformation/productLastLineUtcTime')) pulseLength = float( self.grab_from_xml( 'generalAnnotation/downlinkInformationList/downlinkInformation/downlinkValues/txPulseLength' )) chirpSlope = float( self.grab_from_xml( 'generalAnnotation/downlinkInformationList/downlinkInformation/downlinkValues/txPulseRampRate' )) pulseBandwidth = pulseLength * chirpSlope ####Sentinel is always right looking lookSide = -1 facility = 'EU' version = '1.0' # height = self.product.imageGenerationParameters.sarProcessingInformation._satelliteHeight ####Populate platform platform = self.frame.getInstrument().getPlatform() platform.setPlanet(Planet("Earth")) platform.setMission(mission) platform.setPointingDirection(lookSide) platform.setAntennaLength(2 * azimuthPixelSize) ####Populate instrument instrument = self.frame.getInstrument() instrument.setRadarFrequency(frequency) instrument.setPulseRepetitionFrequency(prf) instrument.setPulseLength(pulseLength) instrument.setChirpSlope(pulseBandwidth / pulseLength) instrument.setIncidenceAngle(incidenceAngle) #self.frame.getInstrument().setRangeBias(0) instrument.setRangePixelSize(rangePixelSize) instrument.setRangeSamplingRate(rangeSamplingRate) instrument.setBeamNumber(swath) instrument.setPulseLength(pulseLength) #Populate Frame #self.frame.setSatelliteHeight(height) self.frame.setSensingStart(dataStartTime) self.frame.setSensingStop(dataStopTime) diffTime = DTUtil.timeDeltaToSeconds(dataStopTime - dataStartTime) / 2.0 sensingMid = dataStartTime + datetime.timedelta( microseconds=int(diffTime * 1e6)) self.frame.setSensingMid(sensingMid) self.frame.setPassDirection(passDirection) self.frame.setPolarization(polarization) self.frame.setStartingRange(startingRange) self.frame.setFarRange(startingRange + (samples - 1) * rangePixelSize) self.frame.setNumberOfLines(lines) self.frame.setNumberOfSamples(samples) self.frame.setProcessingFacility(facility) self.frame.setProcessingSoftwareVersion(version) self.frame.setPassDirection(passDirection) self.extractOrbit() def extractOrbit(self): ''' Extract orbit information from xml node. ''' node = self._xml_root.find('generalAnnotation/orbitList') frameOrbit = self.frame.getOrbit() frameOrbit.setOrbitSource('Header') for child in node.getchildren(): timestamp = self.convertToDateTime(child.find('time').text) pos = [] vel = [] posnode = child.find('position') velnode = child.find('velocity') for tag in ['x', 'y', 'z']: pos.append(float(posnode.find(tag).text)) for tag in ['x', 'y', 'z']: vel.append(float(velnode.find(tag).text)) vec = StateVector() vec.setTime(timestamp) vec.setPosition(pos) vec.setVelocity(vel) frameOrbit.addStateVector(vec) def extractImage(self): """ Use gdal_translate to extract the slc """ import tempfile import subprocess if (not self.gdal_translate): raise TypeError( "The path to executable gdal_translate was not specified") if (not os.path.exists(self.gdal_translate)): raise OSError("Could not find gdal_translate in directory %s" % os.path.dirname(self.gdal_translate)) self.parse() # Use GDAL to convert the geoTIFF file to an raster image # There should be a way to do this using the GDAL python api curdir = os.getcwd() tempdir = tempfile.mkdtemp(dir=curdir) # os.rmdir(tempdir) # Wasteful, but if the directory exists, gdal_translate freaks out #instring = 'RADARSAT_2_CALIB:UNCALIB:%s' % self.xml #process = subprocess.Popen([self.gdal_translate,'-of','MFF2','-ot','CFloat32',instring,tempdir]) if (self.tiff is None) or (not os.path.exists(self.tiff)): raise Exception( 'Path to input tiff file: %s is wrong or file doesnt exist.' % (self.tiff)) process = subprocess.Popen([ self.gdal_translate, self.tiff.strip(), '-of', 'ENVI', '-ot', 'CFloat32', '-co', 'INTERLEAVE=BIP', os.path.join(tempdir, 'image_data') ]) process.wait() # Move the output of the gdal_translate call to a reasonable file name width = self.frame.getNumberOfSamples() lgth = self.frame.getNumberOfLines() os.rename(os.path.join(tempdir, 'image_data'), self.output) # os.unlink(os.path.join(tempdir,'attrib')) os.unlink(os.path.join(tempdir, 'image_data.hdr')) os.rmdir(tempdir) #### slcImage = isceobj.createSlcImage() slcImage.setByteOrder('l') slcImage.setFilename(self.output) slcImage.setAccessMode('read') slcImage.setWidth(self.frame.getNumberOfSamples()) slcImage.setLength(self.frame.getNumberOfLines()) slcImage.setXmin(0) slcImage.setXmax(self.frame.getNumberOfSamples()) self.frame.setImage(slcImage) def extractDoppler(self): ''' self.parse() Extract doppler information as needed by mocomp ''' # ins = self.frame.getInstrument() # dc = self.product.imageGenerationParameters.dopplerCentroid quadratic = {} # r0 = self.frame.startingRange # fs = ins.getRangeSamplingRate() # tNear = 2*r0/Const.c # tMid = tNear + 0.5*self.frame.getNumberOfSamples()/fs # t0 = dc.dopplerCentroidReferenceTime # poly = dc.dopplerCentroidCoefficients # fd_mid = 0.0 # for kk in range(len(poly)): # fd_mid += poly[kk] * (tMid - t0)**kk # quadratic['a'] = fd_mid / ins.getPulseRepetitionFrequency() quadratic['a'] = 0. quadratic['b'] = 0. quadratic['c'] = 0. return quadratic
class UAVSAR_HDF5_SLC(Sensor): """ A class representing a Level1Product meta data. Level1Product(hdf5=h5filename) will parse the hdf5 file and produce an object with attributes for metadata. """ parameter_list = (HDF5, FREQUENCY, POLARIZATION) + Sensor.parameter_list logging_name = 'isce.Sensor.UAVSAR_HDF5_SLC' family = 'uavsar_hdf5_slc' def __init__(self, family='', name=''): # , frequency='frequencyA', polarization='HH'): super(UAVSAR_HDF5_SLC, self).__init__(family if family else self.__class__.family, name=name) self.frame = Frame() self.frame.configure() # Some extra processing parameters unique to UAVSAR HDF5 SLC (currently) self.dopplerRangeTime = [] self.dopplerAzimuthTime = [] self.azimuthRefTime = None self.rangeRefTime = None self.rangeFirstTime = None self.rangeLastTime = None #self.frequency = frequency #self.polarization = polarization self.lookMap = {'right': -1, 'left': 1} return def __getstate__(self): d = dict(self.__dict__) del d['logger'] return d def __setstate__(self, d): self.__dict__.update(d) self.logger = logging.getLogger('isce.Sensor.UAVSAR_HDF5_SLC') return def getFrame(self): return self.frame def parse(self): try: fp = h5py.File(self.hdf5, 'r') except Exception as strerr: self.logger.error("IOError: %s" % strerr) return None self.populateMetadata(fp) fp.close() def populateMetadata(self, file): """ Populate our Metadata objects """ self._populatePlatform(file) self._populateInstrument(file) self._populateFrame(file) self._populateOrbit(file) def _populatePlatform(self, file): platform = self.frame.getInstrument().getPlatform() platform.setMission( file['/science/LSAR/identification'].get('missionId')[( )].decode('utf-8')) platform.setPointingDirection( self.lookMap[file['/science/LSAR/identification'].get( 'lookDirection')[()].decode('utf-8')]) platform.setPlanet(Planet(pname="Earth")) # We are not using this value anywhere. Let's fix it for now. platform.setAntennaLength(12.0) def _populateInstrument(self, file): instrument = self.frame.getInstrument() rangePixelSize = file['/science/LSAR/SLC/swaths/' + self.frequency + '/slantRangeSpacing'][()] wvl = SPEED_OF_LIGHT / file['/science/LSAR/SLC/swaths/' + self.frequency + '/processedCenterFrequency'][()] instrument.setRadarWavelength(wvl) instrument.setPulseRepetitionFrequency( 1.0 / file['/science/LSAR/SLC/swaths/zeroDopplerTimeSpacing'][()]) rangePixelSize = file['/science/LSAR/SLC/swaths/' + self.frequency + '/slantRangeSpacing'][()] instrument.setRangePixelSize(rangePixelSize) # Chrip slope and length only are used in the split spectrum workflow to compute the bandwidth. # Therefore fixing it to 1.0 won't breack anything Chirp_slope = 1.0 rangeBandwidth = file['/science/LSAR/SLC/swaths/' + self.frequency + '/processedRangeBandwidth'][()] Chirp_length = rangeBandwidth / Chirp_slope instrument.setPulseLength(Chirp_length) instrument.setChirpSlope(Chirp_slope) rangeSamplingFrequency = SPEED_OF_LIGHT / 2. / rangePixelSize instrument.setRangeSamplingRate(rangeSamplingFrequency) incangle = 0.0 instrument.setIncidenceAngle(incangle) def _populateFrame(self, file): slantRange = file['/science/LSAR/SLC/swaths/' + self.frequency + '/slantRange'][0] self.frame.setStartingRange(slantRange) referenceUTC = file['/science/LSAR/SLC/swaths/zeroDopplerTime'].attrs[ 'units'].decode('utf-8') referenceUTC = referenceUTC.replace('seconds since ', '') referenceUTC = datetime.datetime.strptime(referenceUTC, '%Y-%m-%d %H:%M:%S') relStart = file['/science/LSAR/SLC/swaths/zeroDopplerTime'][0] relEnd = file['/science/LSAR/SLC/swaths/zeroDopplerTime'][-1] relMid = 0.5 * (relStart + relEnd) sensingStart = self._combineDateTime(referenceUTC, relStart) sensingStop = self._combineDateTime(referenceUTC, relEnd) sensingMid = self._combineDateTime(referenceUTC, relMid) self.frame.setPassDirection( file['/science/LSAR/identification'].get('orbitPassDirection')[( )].decode('utf-8')) self.frame.setOrbitNumber( file['/science/LSAR/identification'].get('trackNumber')[()]) self.frame.setProcessingFacility('JPL') self.frame.setProcessingSoftwareVersion( file['/science/LSAR/SLC/metadata/processingInformation/algorithms'] .get('ISCEVersion')[()].decode('utf-8')) self.frame.setPolarization(self.polarization) self.frame.setNumberOfLines( file['/science/LSAR/SLC/swaths/' + self.frequency + '/' + self.polarization].shape[0]) self.frame.setNumberOfSamples( file['/science/LSAR/SLC/swaths/' + self.frequency + '/' + self.polarization].shape[1]) self.frame.setSensingStart(sensingStart) self.frame.setSensingMid(sensingMid) self.frame.setSensingStop(sensingStop) rangePixelSize = self.frame.instrument.rangePixelSize farRange = slantRange + (self.frame.getNumberOfSamples() - 1) * rangePixelSize self.frame.setFarRange(farRange) def _populateOrbit(self, file): orbit = self.frame.getOrbit() orbit.setReferenceFrame('ECR') orbit.setOrbitSource('Header') referenceUTC = file['/science/LSAR/SLC/swaths/zeroDopplerTime'].attrs[ 'units'].decode('utf-8') referenceUTC = referenceUTC.replace('seconds since ', '') t0 = datetime.datetime.strptime(referenceUTC, '%Y-%m-%d %H:%M:%S') t = file['/science/LSAR/SLC/metadata/orbit/time'] position = file['/science/LSAR/SLC/metadata/orbit/position'] velocity = file['/science/LSAR/SLC/metadata/orbit/velocity'] for i in range(len(position)): vec = StateVector() dt = t0 + datetime.timedelta(seconds=t[i]) vec.setTime(dt) vec.setPosition([position[i, 0], position[i, 1], position[i, 2]]) vec.setVelocity([velocity[i, 0], velocity[i, 1], velocity[i, 2]]) orbit.addStateVector(vec) def extractImage(self): import numpy as np import h5py self.parse() fid = h5py.File(self.hdf5, 'r') ds = fid['/science/LSAR/SLC/swaths/' + self.frequency + '/' + self.polarization] nLines = ds.shape[0] with open(self.output, 'wb') as fout: for ii in range(nLines): ds[ii, :].astype(np.complex64).tofile(fout) fid.close() slcImage = isceobj.createSlcImage() slcImage.setFilename(self.output) slcImage.setXmin(0) slcImage.setXmax(self.frame.getNumberOfSamples()) slcImage.setWidth(self.frame.getNumberOfSamples()) slcImage.setAccessMode('r') slcImage.renderHdr() self.frame.setImage(slcImage) def _parseNanoSecondTimeStamp(self, timestamp): """ Parse a date-time string with nanosecond precision and return a datetime object """ dateTime, nanoSeconds = timestamp.decode('utf-8').split('.') microsec = float(nanoSeconds) * 1e-3 dt = datetime.datetime.strptime(dateTime, '%Y-%m-%d %H:%M:%S') dt = dt + datetime.timedelta(microseconds=microsec) return dt def _combineDateTime(self, dobj, secsstr): '''Takes the date from dobj and time from secs to spit out a date time object. ''' sec = float(secsstr) dt = datetime.timedelta(seconds=sec) return dobj + dt def extractDoppler(self): """ Return the doppler centroid as defined in the HDF5 file. """ import h5py from scipy.interpolate import UnivariateSpline import numpy as np h5 = h5py.File(self.hdf5, 'r') # extract the 2D LUT of Doppler and choose only one range line as the data duplicates for other range lines dop = h5['/science/LSAR/SLC/metadata/processingInformation/parameters/' + self.frequency + '/dopplerCentroid'][0, :] rng = h5[ '/science/LSAR/SLC/metadata/processingInformation/parameters/slantRange'] # extract the slant range of the image grid imgRng = h5['/science/LSAR/SLC/swaths/' + self.frequency + '/slantRange'] # use only part of the slant range that closely covers image ranges and ignore the rest ind0 = np.argmin(np.abs(rng - imgRng[0])) - 1 ind0 = np.max([0, ind0]) ind1 = np.argmin(np.abs(rng - imgRng[-1])) + 1 ind1 = np.min([ind1, rng.shape[0]]) dop = dop[ind0:ind1] rng = rng[ind0:ind1] f = UnivariateSpline(rng, dop) imgDop = f(imgRng) dr = imgRng[1] - imgRng[0] pix = (imgRng - imgRng[0]) / dr fit = np.polyfit(pix, imgDop, 41) self.frame._dopplerVsPixel = list(fit[::-1]) ####insarApp style (doesn't get used for stripmapApp). A fixed Doppler at the middle of the scene quadratic = {} quadratic['a'] = imgDop[int( imgDop.shape[0] / 2)] / self.frame.getInstrument().getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. return quadratic
class Sentinel1(Sensor): """ A Class representing Sentinel1 StripMap data """ family = 's1sm' logging = 'isce.sensor.S1_SM' parameter_list = ( XML, TIFF, MANIFEST, SAFE, ORBIT_FILE, ORBIT_DIR, POLARIZATION, ) + Sensor.parameter_list def __init__(self, family='', name=''): super(Sentinel1, self).__init__(family if family else self.__class__.family, name=name) self.frame = Frame() self.frame.configure() self._xml_root = None def validateUserInputs(self): ''' Validate inputs from user. Populate tiff and xml from SAFE folder name. ''' import fnmatch import zipfile if not self.xml: if not self.safe: raise Exception('SAFE directory is not provided') ####First find annotation file ####Dont need swath number when driving with xml and tiff file if not self.xml: swathid = 's1?-s?-slc-{}'.format(self.polarization) dirname = self.safe if not self.xml: match = None if dirname.endswith('.zip'): pattern = os.path.join('*SAFE', 'annotation', swathid) + '*.xml' zf = zipfile.ZipFile(dirname, 'r') match = fnmatch.filter(zf.namelist(), pattern) zf.close() if (len(match) == 0): raise Exception( 'No annotation xml file found in zip file: {0}'.format( dirname)) ####Add /vsizip at the start to make it a zip file self.xml = '/vsizip/' + os.path.join(dirname, match[0]) else: pattern = os.path.join('annotation', swathid) + '*.xml' match = glob.glob(os.path.join(dirname, pattern)) if (len(match) == 0): raise Exception( 'No annotation xml file found in {0}'.format(dirname)) self.xml = match[0] if not self.xml: raise Exception('No annotation files found') print('Input XML file: ', self.xml) ####Find TIFF file if (not self.tiff) and (self.safe): match = None if dirname.endswith('.zip'): pattern = os.path.join('*SAFE', 'measurement', swathid) + '*.tiff' zf = zipfile.ZipFile(dirname, 'r') match = fnmatch.filter(zf.namelist(), pattern) zf.close() if (len(match) == 0): raise Exception( 'No tiff file found in zip file: {0}'.format(dirname)) ####Add /vsizip at the start to make it a zip file self.tiff = '/vsizip/' + os.path.join(dirname, match[0]) else: pattern = os.path.join('measurement', swathid) + '*.tiff' match = glob.glob(os.path.join(dirname, pattern)) if len(match) == 0: raise Exception( 'No tiff file found in directory: {0}'.format(dirname)) self.tiff = match[0] print('Input TIFF files: ', self.tiff) ####Find manifest files if self.safe: if dirname.endswith('.zip'): pattern = '*SAFE/manifest.safe' zf = zipfile.ZipFile(dirname, 'r') match = fnmatch.filter(zf.namelist(), pattern) zf.close() self.manifest = '/vsizip/' + os.path.join(dirname, match[0]) else: self.manifest = os.path.join(dirname, 'manifest.safe') print('Manifest files: ', self.manifest) return def getFrame(self): return self.frame def parse(self): ''' Actual parsing of the metadata for the product. ''' from isceobj.Sensor.TOPS.Sentinel1 import s1_findOrbitFile ###Check user inputs self.validateUserInputs() if self.xml.startswith('/vsizip'): import zipfile parts = self.xml.split(os.path.sep) if parts[2] == '': parts[2] = os.path.sep zipname = os.path.join(*(parts[2:-3])) fname = os.path.join(*(parts[-3:])) zf = zipfile.ZipFile(zipname, 'r') xmlstr = zf.read(fname) zf.close() else: with open(self.xml, 'r') as fid: xmlstr = fid.read() self._xml_root = ET.fromstring(xmlstr) self.populateMetadata() if self.manifest: self.populateIPFVersion() else: self.frame.setProcessingFacility('ESA') self.frame.setProcessingSoftwareVersion('IPFx.xx') if not self.orbitFile: if self.orbitDir: self.orbitFile = s1_findOrbitFile( self.orbitDir, self.frame.sensingStart, self.frame.sensingStop, mission=self.frame.getInstrument().getPlatform( ).getMission()) if self.orbitFile: orb = self.extractPreciseOrbit() self.frame.orbit.setOrbitSource(os.path.basename(self.orbitFile)) else: orb = self.extractOrbitFromAnnotation() self.frame.orbit.setOrbitSource('Annotation') for sv in orb: self.frame.orbit.addStateVector(sv) def grab_from_xml(self, path): try: res = self._xml_root.find(path).text except: raise Exception('Tag= %s not found' % (path)) if res is None: raise Exception('Tag = %s not found' % (path)) return res def convertToDateTime(self, string): dt = datetime.datetime.strptime(string, "%Y-%m-%dT%H:%M:%S.%f") return dt def populateMetadata(self): """ Create metadata objects from the metadata files """ ####Set each parameter one - by - one mission = self.grab_from_xml('adsHeader/missionId') swath = self.grab_from_xml('adsHeader/swath') polarization = self.grab_from_xml('adsHeader/polarisation') frequency = float( self.grab_from_xml( 'generalAnnotation/productInformation/radarFrequency')) passDirection = self.grab_from_xml( 'generalAnnotation/productInformation/pass') rangePixelSize = float( self.grab_from_xml( 'imageAnnotation/imageInformation/rangePixelSpacing')) azimuthPixelSize = float( self.grab_from_xml( 'imageAnnotation/imageInformation/azimuthPixelSpacing')) rangeSamplingRate = Const.c / (2.0 * rangePixelSize) prf = 1.0 / float( self.grab_from_xml( 'imageAnnotation/imageInformation/azimuthTimeInterval')) lines = int( self.grab_from_xml( 'imageAnnotation/imageInformation/numberOfLines')) samples = int( self.grab_from_xml( 'imageAnnotation/imageInformation/numberOfSamples')) startingRange = float( self.grab_from_xml( 'imageAnnotation/imageInformation/slantRangeTime') ) * Const.c / 2.0 incidenceAngle = float( self.grab_from_xml( 'imageAnnotation/imageInformation/incidenceAngleMidSwath')) dataStartTime = self.convertToDateTime( self.grab_from_xml( 'imageAnnotation/imageInformation/productFirstLineUtcTime')) dataStopTime = self.convertToDateTime( self.grab_from_xml( 'imageAnnotation/imageInformation/productLastLineUtcTime')) pulseLength = float( self.grab_from_xml( 'generalAnnotation/downlinkInformationList/downlinkInformation/downlinkValues/txPulseLength' )) chirpSlope = float( self.grab_from_xml( 'generalAnnotation/downlinkInformationList/downlinkInformation/downlinkValues/txPulseRampRate' )) pulseBandwidth = pulseLength * chirpSlope ####Sentinel is always right looking lookSide = -1 # height = self.product.imageGenerationParameters.sarProcessingInformation._satelliteHeight ####Populate platform platform = self.frame.getInstrument().getPlatform() platform.setPlanet(Planet(pname="Earth")) platform.setMission(mission) platform.setPointingDirection(lookSide) platform.setAntennaLength(2 * azimuthPixelSize) ####Populate instrument instrument = self.frame.getInstrument() instrument.setRadarFrequency(frequency) instrument.setPulseRepetitionFrequency(prf) instrument.setPulseLength(pulseLength) instrument.setChirpSlope(pulseBandwidth / pulseLength) instrument.setIncidenceAngle(incidenceAngle) #self.frame.getInstrument().setRangeBias(0) instrument.setRangePixelSize(rangePixelSize) instrument.setRangeSamplingRate(rangeSamplingRate) instrument.setBeamNumber(swath) instrument.setPulseLength(pulseLength) #Populate Frame #self.frame.setSatelliteHeight(height) self.frame.setSensingStart(dataStartTime) self.frame.setSensingStop(dataStopTime) diffTime = DTUtil.timeDeltaToSeconds(dataStopTime - dataStartTime) / 2.0 sensingMid = dataStartTime + datetime.timedelta( microseconds=int(diffTime * 1e6)) self.frame.setSensingMid(sensingMid) self.frame.setPassDirection(passDirection) self.frame.setPolarization(polarization) self.frame.setStartingRange(startingRange) self.frame.setFarRange(startingRange + (samples - 1) * rangePixelSize) self.frame.setNumberOfLines(lines) self.frame.setNumberOfSamples(samples) self.frame.setPassDirection(passDirection) def extractOrbitFromAnnotation(self): ''' Extract orbit information from xml node. ''' node = self._xml_root.find('generalAnnotation/orbitList') frameOrbit = Orbit() frameOrbit.setOrbitSource('Header') for child in node: timestamp = self.convertToDateTime(child.find('time').text) pos = [] vel = [] posnode = child.find('position') velnode = child.find('velocity') for tag in ['x', 'y', 'z']: pos.append(float(posnode.find(tag).text)) for tag in ['x', 'y', 'z']: vel.append(float(velnode.find(tag).text)) vec = StateVector() vec.setTime(timestamp) vec.setPosition(pos) vec.setVelocity(vel) frameOrbit.addStateVector(vec) planet = self.frame.instrument.platform.planet orbExt = OrbitExtender(planet=planet) orbExt.configure() newOrb = orbExt.extendOrbit(frameOrbit) return newOrb def extractPreciseOrbit(self): ''' Extract precise orbit from given Orbit file. ''' try: fp = open(self.orbitFile, 'r') except IOError as strerr: print("IOError: %s" % strerr) return _xml_root = ET.ElementTree(file=fp).getroot() node = _xml_root.find('Data_Block/List_of_OSVs') orb = Orbit() orb.configure() margin = datetime.timedelta(seconds=40.0) tstart = self.frame.getSensingStart() - margin tend = self.frame.getSensingStop() + margin for child in node: timestamp = self.convertToDateTime(child.find('UTC').text[4:]) if (timestamp >= tstart) and (timestamp < tend): pos = [] vel = [] for tag in ['VX', 'VY', 'VZ']: vel.append(float(child.find(tag).text)) for tag in ['X', 'Y', 'Z']: pos.append(float(child.find(tag).text)) vec = StateVector() vec.setTime(timestamp) vec.setPosition(pos) vec.setVelocity(vel) orb.addStateVector(vec) fp.close() return orb def extractImage(self): """ Use gdal python bindings to extract image """ try: from osgeo import gdal except ImportError: raise Exception( 'GDAL python bindings not found. Need this for RSAT2/ TandemX / Sentinel1A.' ) self.parse() width = self.frame.getNumberOfSamples() lgth = self.frame.getNumberOfLines() src = gdal.Open(self.tiff.strip(), gdal.GA_ReadOnly) band = src.GetRasterBand(1) fid = open(self.output, 'wb') for ii in range(lgth): data = band.ReadAsArray(0, ii, width, 1) data.tofile(fid) fid.close() src = None band = None #### slcImage = isceobj.createSlcImage() slcImage.setByteOrder('l') slcImage.setFilename(self.output) slcImage.setAccessMode('read') slcImage.setWidth(self.frame.getNumberOfSamples()) slcImage.setLength(self.frame.getNumberOfLines()) slcImage.setXmin(0) slcImage.setXmax(self.frame.getNumberOfSamples()) self.frame.setImage(slcImage) def extractDoppler(self): ''' self.parse() Extract doppler information as needed by mocomp ''' from isceobj.Util import Poly1D node = self._xml_root.find('dopplerCentroid/dcEstimateList') tdiff = 1.0e9 dpoly = None for index, burst in enumerate(node): refTime = self.convertToDateTime(burst.find('azimuthTime').text) delta = abs((refTime - self.frame.sensingMid).total_seconds()) if delta < tdiff: tdiff = delta r0 = 0.5 * Const.c * float(burst.find('t0').text) coeffs = [ float(val) for val in burst.find('dataDcPolynomial').text.split() ] poly = Poly1D.Poly1D() poly.initPoly(order=len(coeffs) - 1) poly.setMean(r0) poly.setNorm(0.5 * Const.c) poly.setCoeffs(coeffs) dpoly = poly if dpoly is None: raise Exception( 'Could not extract Doppler information for S1 scene') ###Part for insarApp ###Should be removed in the future rmid = self.frame.startingRange + 0.5 * self.frame.getNumberOfSamples( ) * self.frame.getInstrument().getRangePixelSize() quadratic = {} quadratic['a'] = dpoly( rmid) / self.frame.getInstrument().getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. ###Actual Doppler Polynomial for accurate processing ###Will be used in roiApp pix = np.linspace(0, self.frame.getNumberOfSamples(), num=dpoly._order + 2) rngs = self.frame.startingRange + pix * self.frame.getInstrument( ).getRangePixelSize() evals = dpoly(rngs) fit = np.polyfit(pix, evals, dpoly._order) self.frame._dopplerVsPixel = list(fit[::-1]) print('Doppler Fit : ', fit[::-1]) return quadratic def populateIPFVersion(self): ''' Get IPF version from the manifest file. ''' try: if self.manifest.startswith('/vsizip'): import zipfile parts = self.manifest.split(os.path.sep) if parts[2] == '': parts[2] = os.path.sep zipname = os.path.join(*(parts[2:-2])) fname = os.path.join(*(parts[-2:])) print('MANS: ', zipname, fname) zf = zipfile.ZipFile(zipname, 'r') xmlstr = zf.read(fname) else: with open(self.manifest, 'r') as fid: xmlstr = fid.read() ####Setup namespace nsp = "{http://www.esa.int/safe/sentinel-1.0}" root = ET.fromstring(xmlstr) elem = root.find('.//metadataObject[@ID="processing"]') rdict = elem.find('.//xmlData/' + nsp + 'processing/' + nsp + 'facility').attrib self.frame.setProcessingFacility(rdict['site'] + ', ' + rdict['country']) rdict = elem.find('.//xmlData/' + nsp + 'processing/' + nsp + 'facility/' + nsp + 'software').attrib self.frame.setProcessingSoftwareVersion(rdict['name'] + ' ' + rdict['version']) except: ###Not a critical error ... continuing print( 'Could not read version number successfully from manifest file: ', self.manifest) pass return
class Radarsat1(Component): """ Code to read CEOSFormat leader files for Radarsat-1 SAR data. The tables used to create this parser are based on document number ER-IS-EPO-GS-5902.1 from the European Space Agency. """ auxLength = 50 def __init__(self): Component.__init__(self) self._leaderFile = None self._imageFile = None self._parFile = None self.output = None self.imageFile = None self.leaderFile = None #####Soecific doppler functions for RSAT1 self.doppler_ref_range = None self.doppler_ref_azi = None self.doppler_predict = None self.doppler_DAR = None self.doppler_coeff = None self.frame = Frame() self.frame.configure() self.constants = {'polarization': 'HH', 'antennaLength': 15} self.descriptionOfVariables = {} self.dictionaryOfVariables = { 'LEADERFILE': ['self._leaderFile', 'str', 'mandatory'], 'IMAGEFILE': ['self._imageFile', 'str', 'mandatory'], 'PARFILE': ['self._parFile', 'str', 'optional'], 'OUTPUT': ['self.output', 'str', 'optional'] } def getFrame(self): return self.frame def parse(self): self.leaderFile = LeaderFile(self, file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(self, file=self._imageFile) self.imageFile.parse() self.populateMetadata() def populateMetadata(self): """ Create the appropriate metadata objects from our CEOSFormat metadata """ frame = self._decodeSceneReferenceNumber( self.leaderFile.sceneHeaderRecord. metadata['Scene reference number']) try: rangePixelSize = Const.c / (2 * self.leaderFile.sceneHeaderRecord. metadata['Range sampling rate'] * 1e6) except ZeroDivisionError: rangePixelSize = 0 ins = self.frame.getInstrument() platform = ins.getPlatform() platform.setMission(self.leaderFile.sceneHeaderRecord. metadata['Sensor platform mission identifier']) platform.setAntennaLength(self.constants['antennaLength']) platform.setPointingDirection(-1) platform.setPlanet(Planet('Earth')) ins.setRadarWavelength( self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength']) ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord. metadata['Incidence angle at scene centre']) ##RSAT-1 does not have PRF for raw data in leader file. # self.frame.getInstrument().setPulseRepetitionFrequency(self.leaderFile.sceneHeaderRecord.metadata['Pulse Repetition Frequency']) ins.setRangePixelSize(rangePixelSize) ins.setPulseLength( self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'] * 1e-6) chirpPulseBandwidth = 15.50829e6 # Is this really not in the CEOSFormat Header? ins.setChirpSlope( chirpPulseBandwidth / (self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'] * 1e-6)) ins.setInPhaseValue(7.5) ins.setQuadratureValue(7.5) self.frame.setFrameNumber(frame) self.frame.setOrbitNumber( self.leaderFile.sceneHeaderRecord.metadata['Orbit number']) self.frame.setProcessingFacility( self.leaderFile.sceneHeaderRecord. metadata['Processing facility identifier']) self.frame.setProcessingSystem( self.leaderFile.sceneHeaderRecord. metadata['Processing system identifier']) self.frame.setProcessingSoftwareVersion( self.leaderFile.sceneHeaderRecord. metadata['Processing version identifier']) self.frame.setPolarization(self.constants['polarization']) self.frame.setNumberOfLines( self.imageFile.imageFDR.metadata['Number of lines per data set']) self.frame.setNumberOfSamples( self.imageFile.imageFDR. metadata['Number of pixels per line per SAR channel']) self.frame.getOrbit().setOrbitSource('Header') self.frame.getOrbit().setOrbitQuality( self.leaderFile.platformPositionRecord. metadata['Orbital elements designator']) t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord. metadata['Year of data point'], month=self.leaderFile.platformPositionRecord. metadata['Month of data point'], day=self.leaderFile.platformPositionRecord. metadata['Day of data point']) t0 = t0 + datetime.timedelta( seconds=self.leaderFile.platformPositionRecord. metadata['Seconds of day']) #####Read in orbit in inertial coordinates orb = Orbit() for i in range(self.leaderFile.platformPositionRecord. metadata['Number of data points']): vec = StateVector() t = t0 + datetime.timedelta( seconds=(i * self.leaderFile.platformPositionRecord. metadata['Time interval between DATA points'])) vec.setTime(t) dataPoints = self.leaderFile.platformPositionRecord.metadata[ 'Positional Data Points'][i] vec.setPosition([ dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z'] ]) vec.setVelocity([ dataPoints['Velocity vector X'] / 1000., dataPoints['Velocity vector Y'] / 1000., dataPoints['Velocity vector Z'] / 1000. ]) orb.addStateVector(vec) #####Convert orbits from ECI to ECEF frame. convOrb = ECI2ECEF(orb, eci='ECI_TOD') wgsorb = convOrb.convert() orb = self.frame.getOrbit() for sv in wgsorb: orb.addStateVector(sv) self.parseParFile() def extractImage(self): import isceobj if (self.imageFile is None) or (self.leaderFile is None): self.parse() try: out = open(self.output, 'wb') except IOError as strerr: self.logger.error("IOError: %s" % strerr) self.imageFile.extractImage(output=out) out.close() ####RSAT1 is weird. Contains all useful info in RAW data and not leader. ins = self.frame.getInstrument() ins.setPulseRepetitionFrequency(self.imageFile.prf) ins.setPulseLength(self.imageFile.pulseLength) ins.setRangeSamplingRate(self.imageFile.rangeSamplingRate) ins.setRangePixelSize(Const.c / (2 * self.imageFile.rangeSamplingRate)) ins.setChirpSlope(self.imageFile.chirpSlope) ###### self.frame.setSensingStart(self.imageFile.sensingStart) sensingStop = self.imageFile.sensingStart + datetime.timedelta( seconds=((self.frame.getNumberOfLines() - 1) / self.imageFile.prf)) sensingMid = self.imageFile.sensingStart + datetime.timedelta( seconds=0.5 * (sensingStop - self.imageFile.sensingStart).total_seconds()) self.frame.setSensingStop(sensingStop) self.frame.setSensingMid(sensingMid) self.frame.setNumberOfSamples(self.imageFile.width) self.frame.setStartingRange(self.imageFile.startingRange) farRange = self.imageFile.startingRange + ins.getRangePixelSize( ) * self.imageFile.width * 0.5 self.frame.setFarRange(farRange) rawImage = isceobj.createRawImage() rawImage.setByteOrder('l') rawImage.setAccessMode('read') rawImage.setFilename(self.output) rawImage.setWidth(self.imageFile.width) rawImage.setXmin(0) rawImage.setXmax(self.imageFile.width) rawImage.renderHdr() self.frame.setImage(rawImage) def parseParFile(self): '''Parse the par file if any is available.''' if self._parFile not in (None, ''): par = ParFile(self._parFile) doppinfo = par['prep_block']['sensor']['beam'][ 'DopplerCentroidParameters'] #######Selectively update some values. #######Currently used only for doppler centroids. self.doppler_ref_range = float(doppinfo['reference_range']) self.doppler_ref_azi = datetime.datetime.strptime( doppinfo['reference_date'], '%Y%m%d%H%M%S%f') self.doppler_predict = float(doppinfo['Predict_doppler']) self.doppler_DAR = float(doppinfo['DAR_doppler']) coeff = doppinfo['doppler_centroid_coefficients'] rngOrder = int(coeff['number_of_coefficients_first_dimension']) azOrder = int(coeff['number_of_coefficients_second_dimension']) self.doppler_coeff = Polynomial(rangeOrder=rngOrder, azimuthOrder=azOrder) self.doppler_coeff.setMeanRange(self.doppler_ref_range) self.doppler_coeff.setMeanAzimuth( secondsSinceMidnight(self.doppler_ref_azi)) for ii in range(azOrder): for jj in range(rngOrder): key = 'a%d%d' % (ii, jj) val = float(coeff[key]) self.doppler_coeff.setCoeff(ii, jj, val) def extractDoppler(self): ''' Evaluate the doppler polynomial and return the average value for now. ''' rmin = self.frame.getStartingRange() rmax = self.frame.getFarRange() rmid = 0.5 * (rmin + rmax) azmid = secondsSinceMidnight(self.frame.getSensingMid()) print(rmid, self.doppler_coeff.getMeanRange()) print(azmid, self.doppler_coeff.getMeanAzimuth()) if self.doppler_coeff is None: raise Exception( 'ASF PARFILE was not provided. Cannot determine default doppler.' ) dopav = self.doppler_coeff(azmid, rmid) prf = self.frame.getInstrument().getPulseRepetitionFrequency() quadratic = {} quadratic['a'] = dopav / prf quadratic['b'] = 0. quadratic['c'] = 0. return quadratic def _decodeSceneReferenceNumber(self, referenceNumber): return referenceNumber
class ERS(Component): #Parsers.CEOS.CEOSFormat.ceosTypes['text'] = # {'typeCode': 63, 'subtypeCode': [18,18,18]} #Parsers.CEOS.CEOSFormat.ceosTypes['leaderFile'] = # {'typeCode': 192, 'subtypeCode': [63,18,18]} #Parsers.CEOS.CEOSFormat.ceosTypes['dataSetSummary'] = # {'typeCode': 10, 'subtypeCode': [10,31,20]} #Parsers.CEOS.CEOSFormat.ceosTypes['platformPositionData'] = # {'typeCode': 30, 'subtypeCode': [10,31,20]} #Parsers.CEOS.CEOSFormat.ceosTypes['facilityData'] = # {'typeCode': 200, 'subtypeCode': [10,31,50]} #Parsers.CEOS.CEOSFormat.ceosTypes['datafileDescriptor'] = # {'typeCode': 192, 'subtypeCode':[63,18,18]} #Parsers.CEOS.CEOSFormat.ceosTypes['signalData'] = # {'typeCode': 10, 'subtypeCode': [50,31,20]} #Parsers.CEOS.CEOSFormat.ceosTypes['nullFileDescriptor'] = # {'typeCode': 192, 'subtypeCode': [192,63,18]} logging_name = 'isce.sensor.ers' def __init__(self): Component.__init__(self) self._leaderFile = None self._imageFileList = '' self._leaderFileList = '' self._imageFile = None self._orbitDir = None # Use this for Delft Orbit files self._orbitFile = None # Use this for PDS Orbit files for now self._orbitType = None self.frameList = [] self.output = None self.descriptionOfVariables = {} self.dictionaryOfVariables = { 'ORBIT_TYPE': ['self._orbitType','str','mandatory'], 'ORBIT_DIRECTORY': ['self._orbitDir','str','optional'], 'ORBIT_FILE': ['self._orbitFile','str','optional'], 'LEADERFILE': ['self._leaderFileList','str','mandatory'], 'IMAGEFILE': ['self._imageFileList','str','mandatory'], 'OUTPUT': ['self.output','str','optional']} self.frame = Frame() self.frame.configure() # Constants are from # J. J. Mohr and S. N. Madsen. Geometric calibration of ERS satellite # SAR images. IEEE T. Geosci. Remote, 39(4):842-850, Apr. 2001. self.constants = {'polarization': 'VV', 'antennaLength': 10, 'lookDirection': 'RIGHT', 'chirpPulseBandwidth': 15.50829e6, 'rangeSamplingRate': 18.962468e6, 'delayTime':6.622e-6, 'iBias': 15.5, 'qBias': 15.5} return None def getFrame(self): return self.frame def parse(self): self.leaderFile = LeaderFile(file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(self) self.imageFile.parse() self.populateMetadata() def populateMetadata(self): """ Create the appropriate metadata objects from our CEOSFormat metadata """ self._populatePlatform() self._populateInstrument() self._populateFrame() if (self._orbitType == 'ODR'): self._populateDelftOrbits() elif (self._orbitType == 'PRC'): self._populatePRCOrbits() elif (self._orbitType == 'PDS'): self._populatePDSOrbits() else: self._populateHeaderOrbit() def _populatePlatform(self): """ Populate the platform object with metadata """ platform = self.frame.getInstrument().getPlatform() platform.setMission(self.leaderFile.sceneHeaderRecord.metadata[ 'Sensor platform mission identifier']) platform.setAntennaLength(self.constants['antennaLength']) platform.setPointingDirection(-1) platform.setPlanet(Planet('Earth')) def _populateInstrument(self): """Populate the instrument object with metadata""" instrument = self.frame.getInstrument() pri = self.imageFile.firstPri rangeSamplingRate = self.constants['rangeSamplingRate'] #rangeSamplingRate = self.leaderFile.sceneHeaderRecord.metadata[ # 'Range sampling rate']*1e6 rangePixelSize = Const.c/(2.0*rangeSamplingRate) pulseInterval = 4.0/rangeSamplingRate*(pri+2.0) prf = 1.0/pulseInterval instrument.setRadarWavelength( self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength']) instrument.setIncidenceAngle( self.leaderFile.sceneHeaderRecord.metadata[ 'Incidence angle at scene centre']) instrument.setPulseRepetitionFrequency(prf) instrument.setRangeSamplingRate(rangeSamplingRate) instrument.setRangePixelSize(rangePixelSize) instrument.setPulseLength(self.leaderFile.sceneHeaderRecord.metadata[ 'Range pulse length']*1e-6) instrument.setChirpSlope(self.constants['chirpPulseBandwidth']/ (self.leaderFile.sceneHeaderRecord.metadata['Range pulse length']* 1e-6)) instrument.setInPhaseValue(self.constants['iBias']) instrument.setQuadratureValue(self.constants['qBias']) def _populateFrame(self): """Populate the scene object with metadata""" rangeSamplingRate = self.constants['rangeSamplingRate'] #rangeSamplingRate = self.leaderFile.sceneHeaderRecord.metadata[ # 'Range sampling rate']*1e6 rangePixelSize = Const.c/(2.0*rangeSamplingRate) pulseInterval = 1.0/self.frame.getInstrument().getPulseRepetitionFrequency() frame = self._decodeSceneReferenceNumber( self.leaderFile.sceneHeaderRecord.metadata[ 'Scene reference number']) startingRange = (9*pulseInterval + self.imageFile.minSwst*4/rangeSamplingRate-self.constants['delayTime'])*Const.c/2.0 farRange = startingRange + self.imageFile.width*rangePixelSize # Use the Scene center time to get the date, then use the ICU on board time from the image for the rest centerLineTime = datetime.datetime.strptime(self.leaderFile.sceneHeaderRecord.metadata['Scene centre time'],"%Y%m%d%H%M%S%f") first_line_utc = datetime.datetime(year=centerLineTime.year, month=centerLineTime.month, day=centerLineTime.day) if(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier'] in ('CRDC_SARDPF','GTS - ERS')): first_line_utc = first_line_utc + datetime.timedelta(milliseconds=self.imageFile.startTime) else: deltaSeconds = (self.imageFile.startTime - self.leaderFile.sceneHeaderRecord.metadata['Satellite encoded binary time code'])* 1/256.0 # Sometimes, the ICU on board clock is corrupt, if the time suggested by the on board clock is more than # 5 days from the satellite clock time, assume its bogus and use the low-precision scene centre time if (math.fabs(deltaSeconds) > 5*86400): self.logger.warn("ICU on board time appears to be corrupt, resorting to low precision clock") first_line_utc = centerLineTime - datetime.timedelta(microseconds=pulseInterval*(self.imageFile.length/2.0)*1e6) else: satelliteClockTime = datetime.datetime.strptime(self.leaderFile.sceneHeaderRecord.metadata['Satellite clock time'],"%Y%m%d%H%M%S%f") first_line_utc = satelliteClockTime + datetime.timedelta(microseconds=int(deltaSeconds*1e6)) mid_line_utc = first_line_utc + datetime.timedelta(microseconds=pulseInterval*(self.imageFile.length/2.0)*1e6) last_line_utc = first_line_utc + datetime.timedelta(microseconds=pulseInterval*self.imageFile.length*1e6) self.logger.debug("Frame UTC start, mid, end times: %s %s %s" % (first_line_utc,mid_line_utc,last_line_utc)) self.frame.setFrameNumber(frame) self.frame.setOrbitNumber(self.leaderFile.sceneHeaderRecord.metadata['Orbit number']) self.frame.setStartingRange(startingRange) self.frame.setFarRange(farRange) self.frame.setProcessingFacility(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier']) self.frame.setProcessingSystem(self.leaderFile.sceneHeaderRecord.metadata['Processing system identifier']) self.frame.setProcessingSoftwareVersion(self.leaderFile.sceneHeaderRecord.metadata['Processing version identifier']) self.frame.setPolarization(self.constants['polarization']) self.frame.setNumberOfLines(self.imageFile.length) self.frame.setNumberOfSamples(self.imageFile.width) self.frame.setSensingStart(first_line_utc) self.frame.setSensingMid(mid_line_utc) self.frame.setSensingStop(last_line_utc) def _populateHeaderOrbit(self): """Populate an orbit object with the header orbits""" self.logger.info("Using Header Orbits") orbit = self.frame.getOrbit() orbit.setOrbitSource('Header') orbit.setOrbitQuality('Unknown') t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord.metadata['Year of data point'], month=self.leaderFile.platformPositionRecord.metadata['Month of data point'], day=self.leaderFile.platformPositionRecord.metadata['Day of data point']) t0 = t0 + datetime.timedelta(microseconds=self.leaderFile.platformPositionRecord.metadata['Seconds of day']*1e6) for i in range(self.leaderFile.platformPositionRecord.metadata['Number of data points']): vec = StateVector() deltaT = self.leaderFile.platformPositionRecord.metadata['Time interval between DATA points'] t = t0 + datetime.timedelta(microseconds=i*deltaT*1e6) vec.setTime(t) dataPoints = self.leaderFile.platformPositionRecord.metadata['Positional Data Points'][i] vec.setPosition([dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z']]) vec.setVelocity([dataPoints['Velocity vector X'], dataPoints['Velocity vector Y'], dataPoints['Velocity vector Z']]) orbit.addStateVector(vec) def _populateDelftOrbits(self): """Populate an orbit object with the Delft orbits""" from isceobj.Orbit.ODR import ODR, Arclist self.logger.info("Using Delft Orbits") arclist = Arclist(os.path.join(self._orbitDir,'arclist')) arclist.parse() orbitFile = arclist.getOrbitFile(self.frame.getSensingStart()) odr = ODR(file=os.path.join(self._orbitDir,orbitFile)) #jng it seem that for this tipe of orbit points are separated by 60 sec. In ODR at least 9 state vectors are needed to compute the velocities. add # extra time before and after to allow interpolation, but do not do it for all data points. too slow startTimePreInterp = self.frame.getSensingStart() - datetime.timedelta(minutes=60) stopTimePreInterp = self.frame.getSensingStop() + datetime.timedelta(minutes=60) odr.parseHeader(startTimePreInterp,stopTimePreInterp) startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) orbit = odr.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def _populatePRCOrbits(self): """Populate an orbit object the D-PAF PRC orbits""" from isceobj.Orbit.PRC import PRC, Arclist self.logger.info("Using PRC Orbits") arclist = Arclist(os.path.join(self._orbitDir,'arclist')) arclist.parse() orbitFile = arclist.getOrbitFile(self.frame.getSensingStart()) self.logger.debug("Using file %s" % (orbitFile)) prc = PRC(file=os.path.join(self._orbitDir,orbitFile)) prc.parse() startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) fullOrbit = prc.getOrbit() orbit = fullOrbit.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def _populatePDSOrbits(self): """ Populate an orbit object using the ERS-2 PDS format """ from isceobj.Orbit.PDS import PDS self.logger.info("Using PDS Orbits") pds = PDS(file=self._orbitFile) pds.parse() startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) fullOrbit = pds.getOrbit() orbit = fullOrbit.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def extractImage(self): import array import math # just in case there was only one image and it was passed as a str instead of a list with only one element if(isinstance(self._imageFileList,str)): self._imageFileList = [self._imageFileList] self._leaderFileList = [self._leaderFileList] if(len(self._imageFileList) != len(self._leaderFileList)): self.logger.error("Number of leader files different from number of image files.") raise Exception self.frameList = [] for i in range(len(self._imageFileList)): appendStr = "_" + str(i) #if only one file don't change the name if(len(self._imageFileList) == 1): appendStr = '' self.frame = Frame() self.frame.configure() self._leaderFile = self._leaderFileList[i] self._imageFile = self._imageFileList[i] self.leaderFile = LeaderFile(file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(self) try: outputNow = self.output + appendStr out = open(outputNow,'wb') except IOError as strerr: self.logger.error("IOError: %s" % strerr) return self.imageFile.extractImage(output=out) out.close() rawImage = isceobj.createRawImage() rawImage.setByteOrder('l') rawImage.setAccessMode('read') rawImage.setFilename(outputNow) rawImage.setWidth(self.imageFile.width) rawImage.setXmin(0) rawImage.setXmax(self.imageFile.width) self.frame.setImage(rawImage) self.populateMetadata() self.frameList.append(self.frame) #jng Howard Z at this point adjusts the sampling starting time for imagery generated from CRDC_SARDPF facility. # for now create the orbit aux file based in starting time and prf prf = self.frame.getInstrument().getPulseRepetitionFrequency() senStart = self.frame.getSensingStart() numPulses = int(math.ceil(DTU.timeDeltaToSeconds(self.frame.getSensingStop()-senStart)*prf)) # the aux files has two entries per line. day of the year and microseconds in the day musec0 = (senStart.hour*3600 + senStart.minute*60 + senStart.second)*10**6 + senStart.microsecond maxMusec = (24*3600)*10**6#use it to check if we went across a day. very rare day0 = (datetime.datetime(senStart.year,senStart.month,senStart.day) - datetime.datetime(senStart.year,1,1)).days + 1 outputArray = array.array('d',[0]*2*numPulses) self.frame.auxFile = outputNow + '.aux' fp = open(self.frame.auxFile,'wb') j = -1 for i1 in range(numPulses): j += 1 musec = round((j/prf)*10**6) + musec0 if musec >= maxMusec: day0 += 1 musec0 = musec%maxMusec musec = musec0 j = 0 outputArray[2*i1] = day0 outputArray[2*i1+1] = musec outputArray.tofile(fp) fp.close() tk = Track() if(len(self._imageFileList) > 1): self.frame = tk.combineFrames(self.output,self.frameList) for i in range(len(self._imageFileList)): try: os.remove(self.output + "_" + str(i)) except OSError: print("Error. Cannot remove temporary file",self.output + "_" + str(i)) raise OSError def _decodeSceneReferenceNumber(self,referenceNumber): frameNumber = referenceNumber.split('=') if (len(frameNumber) > 2): frameNumber = frameNumber[2].strip() else: frameNumber = frameNumber[0] return frameNumber
class SAOCOM_SLC(Sensor): parameter_list = (IMAGEFILE, XEMTFILE, XMLFILE) + Sensor.parameter_list """ A Class for parsing SAOCOM instrument and imagery files """ family = 'saocom_slc' def __init__(self,family='',name=''): super(SAOCOM_SLC, self).__init__(family if family else self.__class__.family, name=name) self._imageFile = None self._xemtFileParser = None self._xmlFileParser = None self._instrumentFileData = None self._imageryFileData = None self.dopplerRangeTime = None self.rangeRefTime = None self.azimuthRefTime = None self.rangeFirstTime = None self.rangeLastTime = None self.logger = logging.getLogger("isce.sensor.SAOCOM_SLC") self.frame = None self.frameList = [] self.lookMap = {'RIGHT': -1, 'LEFT': 1} self.nearIncidenceAngle = {'S1DP': 20.7, 'S2DP': 24.9, 'S3DP': 29.1, 'S4DP': 33.7, 'S5DP': 38.2, 'S6DP': 41.3, 'S7DP': 44.6, 'S8DP': 47.2, 'S9DP': 48.8, 'S1QP': 17.6, 'S2QP': 19.5, 'S3QP': 21.4, 'S4QP': 23.2, 'S5QP': 25.3, 'S6QP': 27.2, 'S7QP': 29.6, 'S8QP': 31.2, 'S9QP': 33.0, 'S10QP': 34.6} self.farIncidenceAngle = {'S1DP': 25.0, 'S2DP': 29.2, 'S3DP': 33.8, 'S4DP': 38.3, 'S5DP': 41.3, 'S6DP': 44.5, 'S7DP': 47.1, 'S8DP': 48.7, 'S9DP': 50.2, 'S1QP': 19.6, 'S2QP': 21.5, 'S3QP': 23.3, 'S4QP': 25.4, 'S5QP': 27.3, 'S6QP': 29.6, 'S7QP': 31.2, 'S8QP': 33.0, 'S9QP': 34.6, 'S10QP': 35.5} def parse(self): """ Parse both imagery and instrument files and create objects representing the platform, instrument and scene """ self.frame = Frame() self.frame.configure() self._xemtFileParser = XEMTFile(fileName=self.xemtFile) self._xemtFileParser.parse() self._xmlFileParser = XMLFile(fileName=self.xmlFile) self._xmlFileParser.parse() self.populateMetadata() def populateMetadata(self): self._populatePlatform() self._populateInstrument() self._populateFrame() self._populateOrbit() self._populateExtras() def _populatePlatform(self): """Populate the platform object with metadata""" platform = self.frame.getInstrument().getPlatform() # Populate the Platform and Scene objects platform.setMission(self._xmlFileParser.sensorName) platform.setPointingDirection(self.lookMap[self._xmlFileParser.sideLooking]) platform.setAntennaLength(9.968) platform.setPlanet(Planet(pname="Earth")) def _populateInstrument(self): """Populate the instrument object with metadata""" instrument = self.frame.getInstrument() rangePixelSize = self._xmlFileParser.PSRng azimuthPixelSize = self._xmlFileParser.PSAz radarWavelength = Const.c/float(self._xmlFileParser.fc_hz) instrument.setRadarWavelength(radarWavelength) instrument.setPulseRepetitionFrequency(self._xmlFileParser.prf) instrument.setRangePixelSize(rangePixelSize) instrument.setAzimuthPixelSize(azimuthPixelSize) instrument.setPulseLength(self._xmlFileParser.pulseLength) instrument.setChirpSlope(float(self._xmlFileParser.pulseBandwidth)/float(self._xmlFileParser.pulseLength)) instrument.setRangeSamplingRate(self._xmlFileParser.frg) incAngle = 0.5*(self.nearIncidenceAngle[self._xemtFileParser.beamID] + self.farIncidenceAngle[self._xemtFileParser.beamID]) instrument.setIncidenceAngle(incAngle) def _populateFrame(self): """Populate the scene object with metadata""" rft = self._xmlFileParser.rangeStartTime slantRange = float(rft)*Const.c/2.0 self.frame.setStartingRange(slantRange) sensingStart = self._parseNanoSecondTimeStamp(self._xmlFileParser.azimuthStartTime) sensingTime = self._xmlFileParser.lines/self._xmlFileParser.prf sensingStop = sensingStart + datetime.timedelta(seconds=sensingTime) sensingMid = sensingStart + datetime.timedelta(seconds=0.5*sensingTime) self.frame.setPassDirection(self._xmlFileParser.orbitDirection) self.frame.setProcessingFacility(self._xemtFileParser.facilityID) self.frame.setProcessingSoftwareVersion(self._xemtFileParser.softVersion) self.frame.setPolarization(self._xmlFileParser.polarization) self.frame.setNumberOfLines(self._xmlFileParser.lines) self.frame.setNumberOfSamples(self._xmlFileParser.samples) self.frame.setSensingStart(sensingStart) self.frame.setSensingMid(sensingMid) self.frame.setSensingStop(sensingStop) rangePixelSize = self.frame.getInstrument().getRangePixelSize() farRange = slantRange + (self.frame.getNumberOfSamples()-1)*rangePixelSize self.frame.setFarRange(farRange) def _populateOrbit(self): orbit = self.frame.getOrbit() orbit.setReferenceFrame('ECR') orbit.setOrbitSource('Header') t0 = self._parseNanoSecondTimeStamp(self._xmlFileParser.orbitStartTime) t = np.arange(self._xmlFileParser.numberSV)*self._xmlFileParser.deltaTimeSV position = self._xmlFileParser.orbitPositionXYZ velocity = self._xmlFileParser.orbitVelocityXYZ for i in range(0,self._xmlFileParser.numberSV): vec = StateVector() dt = t0 + datetime.timedelta(seconds=t[i]) vec.setTime(dt) vec.setPosition([position[i*3],position[i*3+1],position[i*3+2]]) vec.setVelocity([velocity[i*3],velocity[i*3+1],velocity[i*3+2]]) orbit.addStateVector(vec) print("valor "+str(i)+": "+str(dt)) def _populateExtras(self): from isceobj.Doppler.Doppler import Doppler self.dopplerRangeTime = self._xmlFileParser.dopRngTime self.rangeRefTime = self._xmlFileParser.trg self.rangeFirstTime = self._xmlFileParser.rangeStartTime def extractImage(self): """ Exports GeoTiff to ISCE format. """ from osgeo import gdal ds = gdal.Open(self._imageFileName) metadata = ds.GetMetadata() geoTs = ds.GetGeoTransform() #GeoTransform prj = ds.GetProjection() #Projection dataType = ds.GetRasterBand(1).DataType gcps = ds.GetGCPs() sds = ds.ReadAsArray() # Output raster array to ISCE file driver = gdal.GetDriverByName('ISCE') export = driver.Create(self.output, ds.RasterXSize, ds.RasterYSize, 1, dataType) band = export.GetRasterBand(1) band.WriteArray(sds) export.SetGeoTransform(geoTs) export.SetMetadata(metadata) export.SetProjection(prj) export.SetGCPs(gcps,prj) band.FlushCache() export.FlushCache() self.parse() slcImage = isceobj.createSlcImage() slcImage.setFilename(self.output) slcImage.setXmin(0) slcImage.setXmax(self.frame.getNumberOfSamples()) slcImage.setWidth(self.frame.getNumberOfSamples()) slcImage.setAccessMode('r') self.frame.setImage(slcImage) def _parseNanoSecondTimeStamp(self,timestamp): """ Parse a date-time string with microsecond precision and return a datetime object """ dateTime,decSeconds = timestamp.split('.') microsec = float("0."+decSeconds)*1e6 dt = datetime.datetime.strptime(dateTime,'%d-%b-%Y %H:%M:%S') dt = dt + datetime.timedelta(microseconds=microsec) return dt def extractDoppler(self): """ Return the doppler centroid. """ quadratic = {} r0 = self.frame.getStartingRange() dr = self.frame.instrument.getRangePixelSize() width = self.frame.getNumberOfSamples() midr = r0 + (width/2.0) * dr midtime = 2 * midr/ Const.c - self.rangeRefTime fd_mid = 0.0 tpow = midtime for kk in self.dopplerRangeTime: fd_mid += kk * tpow tpow *= midtime ####For insarApp quadratic['a'] = fd_mid/self.frame.getInstrument().getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. ####For roiApp ####More accurate from isceobj.Util import Poly1D coeffs = self.dopplerRangeTime dr = self.frame.getInstrument().getRangePixelSize() rref = 0.5 * Const.c * self.rangeRefTime r0 = self.frame.getStartingRange() norm = 0.5*Const.c/dr dcoeffs = [] for ind, val in enumerate(coeffs): dcoeffs.append( val / (norm**ind)) poly = Poly1D.Poly1D() poly.initPoly(order=len(coeffs)-1) poly.setMean( (rref - r0)/dr - 1.0) poly.setCoeffs(dcoeffs) pix = np.linspace(0, self.frame.getNumberOfSamples(), num=len(coeffs)+1) evals = poly(pix) fit = np.polyfit(pix,evals, len(coeffs)-1) self.frame._dopplerVsPixel = list(fit[::-1]) print('Doppler Fit: ', fit[::-1]) return quadratic
class ALOS_SLC(Sensor): """ Code to read CEOSFormat leader files for ALOS SLC data. """ parameter_list = (WAVELENGTH, LEADERFILE, IMAGEFILE) + Sensor.parameter_list family = 'alos_slc' logging_name = 'isce.sensor.ALOS_SLC' #Orbital Elements (Quality) Designator #ALOS-2/PALSAR-2 Level 1.1/1.5/2.1/3.1 CEOS SAR Product Format Description #PALSAR-2_xx_Format_CEOS_E_r.pdf orbitElementsDesignator = {'0': 'preliminary', '1': 'decision', '2': 'high precision'} def __init__(self, name=''): super().__init__(family=self.__class__.family, name=name) self.imageFile = None self.leaderFile = None # Specific doppler functions for ALOS self.doppler_coeff = None self.azfmrate_coeff = None self.lineDirection = None self.pixelDirection = None self.frame = Frame() self.frame.configure() self.constants = {'antennaLength': 15} def getFrame(self): return self.frame def parse(self): self.leaderFile = LeaderFile(self, file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(self, file=self._imageFile) self.imageFile.parse() self.populateMetadata() self._populateExtras() def populateMetadata(self): """ Create the appropriate metadata objects from our CEOSFormat metadata """ frame = self._decodeSceneReferenceNumber(self.leaderFile.sceneHeaderRecord.metadata['Scene reference number']) fsamplookup = self.leaderFile.sceneHeaderRecord.metadata['Range sampling rate in MHz']*1.0e6 rangePixelSize = Const.c/(2*fsamplookup) ins = self.frame.getInstrument() platform = ins.getPlatform() platform.setMission(self.leaderFile.sceneHeaderRecord.metadata['Sensor platform mission identifier']) platform.setAntennaLength(self.constants['antennaLength']) platform.setPointingDirection(1) platform.setPlanet(Planet(pname='Earth')) if self.wavelength: ins.setRadarWavelength(float(self.wavelength)) else: ins.setRadarWavelength(self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength']) ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord.metadata['Incidence angle at scene centre']) self.frame.getInstrument().setPulseRepetitionFrequency(self.leaderFile.sceneHeaderRecord.metadata['Pulse Repetition Frequency in mHz']*1.0e-3) ins.setRangePixelSize(rangePixelSize) ins.setRangeSamplingRate(fsamplookup) ins.setPulseLength(self.leaderFile.sceneHeaderRecord.metadata['Range pulse length in microsec']*1.0e-6) chirpSlope = self.leaderFile.sceneHeaderRecord.metadata['Nominal range pulse (chirp) amplitude coefficient linear term'] chirpPulseBandwidth = abs(chirpSlope * self.leaderFile.sceneHeaderRecord.metadata['Range pulse length in microsec']*1.0e-6) ins.setChirpSlope(chirpSlope) ins.setInPhaseValue(7.5) ins.setQuadratureValue(7.5) self.lineDirection = self.leaderFile.sceneHeaderRecord.metadata['Time direction indicator along line direction'].strip() self.pixelDirection = self.leaderFile.sceneHeaderRecord.metadata['Time direction indicator along pixel direction'].strip() ######ALOS includes this information in clock angle clockAngle = self.leaderFile.sceneHeaderRecord.metadata['Sensor clock angle'] if clockAngle == 90.0: platform.setPointingDirection(-1) elif clockAngle == -90.0: platform.setPointingDirection(1) else: raise Exception('Unknown look side. Clock Angle = {0}'.format(clockAngle)) self.frame.setFrameNumber(frame) self.frame.setOrbitNumber(self.leaderFile.sceneHeaderRecord.metadata['Orbit number']) self.frame.setProcessingFacility(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier']) self.frame.setProcessingSystem(self.leaderFile.sceneHeaderRecord.metadata['Processing system identifier']) self.frame.setProcessingSoftwareVersion(self.leaderFile.sceneHeaderRecord.metadata['Processing version identifier']) self.frame.setNumberOfLines(self.imageFile.imageFDR.metadata['Number of lines per data set']) self.frame.setNumberOfSamples(self.imageFile.imageFDR.metadata['Number of pixels per line per SAR channel']) self.frame.instrument.setAzimuthPixelSize(self.leaderFile.dataQualitySummaryRecord.metadata['Azimuth resolution']) ###### orb = self.frame.getOrbit() orb.setOrbitSource('Header') orb.setOrbitQuality( self.orbitElementsDesignator[ self.leaderFile.platformPositionRecord.metadata['Orbital elements designator'] ] ) t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord.metadata['Year of data point'], month=self.leaderFile.platformPositionRecord.metadata['Month of data point'], day=self.leaderFile.platformPositionRecord.metadata['Day of data point']) t0 = t0 + datetime.timedelta(seconds=self.leaderFile.platformPositionRecord.metadata['Seconds of day']) #####Read in orbit in inertial coordinates deltaT = self.leaderFile.platformPositionRecord.metadata['Time interval between data points'] numPts = self.leaderFile.platformPositionRecord.metadata['Number of data points'] orb = self.frame.getOrbit() for i in range(numPts): vec = StateVector() t = t0 + datetime.timedelta(seconds=i*deltaT) vec.setTime(t) dataPoints = self.leaderFile.platformPositionRecord.metadata['Positional Data Points'][i] pos = [dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z']] vel = [dataPoints['Velocity vector X'], dataPoints['Velocity vector Y'], dataPoints['Velocity vector Z']] vec.setPosition(pos) vec.setVelocity(vel) orb.addStateVector(vec) self.doppler_coeff = [self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid constant term'], self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid linear term'], self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid quadratic term']] self.azfmrate_coeff = [self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency rate constant term'], self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency rate linear term'], self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency rate quadratic term']] def _populateExtras(self): dataset = self.leaderFile.radiometricRecord.metadata print("Record Number: %d" % (dataset["Record Number"])) print("First Record Subtype: %d" % (dataset["First Record Subtype"])) print("Record Type Code: %d" % (dataset["Record Type Code"])) print("Second Record Subtype: %d" % (dataset["Second Record Subtype"])) print("Third Record Subtype: %d" % (dataset["Third Record Subtype"])) print("Record Length: %d" % (dataset["Record Length"])) print("SAR channel indicator: %d" % (dataset["SAR channel indicator"])) print("Number of data sets: %d" % (dataset["Number of data sets"])) numPts = dataset['Number of data sets'] for i in range(numPts): if i > 1: break print('Radiometric record field: %d' % (i+1)) dataset = self.leaderFile.radiometricRecord.metadata[ 'Radiometric data sets'][i] DT11 = complex(dataset['Real part of DT 1,1'], dataset['Imaginary part of DT 1,1']) DT12 = complex(dataset['Real part of DT 1,2'], dataset['Imaginary part of DT 1,2']) DT21 = complex(dataset['Real part of DT 2,1'], dataset['Imaginary part of DT 2,1']) DT22 = complex(dataset['Real part of DT 2,2'], dataset['Imaginary part of DT 2,2']) DR11 = complex(dataset['Real part of DR 1,1'], dataset['Imaginary part of DR 1,1']) DR12 = complex(dataset['Real part of DR 1,2'], dataset['Imaginary part of DR 1,2']) DR21 = complex(dataset['Real part of DR 2,1'], dataset['Imaginary part of DR 2,1']) DR22 = complex(dataset['Real part of DR 2,2'], dataset['Imaginary part of DR 2,2']) print("Calibration factor [dB]: %f" % (dataset["Calibration factor"])) print('Distortion matrix Trasmission [DT11, DT12, DT21, DT22]: ' '[%s, %s, %s, %s]' % (str(DT11), str(DT12), str(DT21), str(DT22))) print('Distortion matrix Reception [DR11, DR12, DR21, DR22]: ' '[%s, %s, %s, %s]' % (str(DR11), str(DR12), str(DR21), str(DR22))) self.transmit = Distortion(DT12, DT21, DT22) self.receive = Distortion(DR12, DR21, DR22) self.calibrationFactor = float( dataset['Calibration factor']) def extractImage(self): import isceobj if (self.imageFile is None) or (self.leaderFile is None): self.parse() try: out = open(self.output, 'wb') except IOError as strerr: self.logger.error("IOError: %s" % strerr) self.imageFile.extractImage(output=out) out.close() self.frame.setSensingStart(self.imageFile.sensingStart) self.frame.setSensingStop(self.imageFile.sensingStop) sensingMid = self.imageFile.sensingStart + datetime.timedelta(seconds = 0.5* (self.imageFile.sensingStop - self.imageFile.sensingStart).total_seconds()) self.frame.setSensingMid(sensingMid) try: rngGate= Const.c*0.5*self.leaderFile.sceneHeaderRecord.metadata['Range gate delay in microsec']*1e-6 except: rngGate = None if (rngGate is None) or (rngGate == 0.0): rngGate = self.imageFile.nearRange self.frame.setStartingRange(rngGate) self.frame.getInstrument().setPulseRepetitionFrequency(self.imageFile.prf) pixelSize = self.frame.getInstrument().getRangePixelSize() farRange = self.imageFile.nearRange + (pixelSize-1) * self.imageFile.width self.frame.setFarRange(farRange) self.frame.setPolarization(self.imageFile.current_polarization) rawImage = isceobj.createSlcImage() rawImage.setByteOrder('l') rawImage.setAccessMode('read') rawImage.setFilename(self.output) rawImage.setWidth(self.imageFile.width) rawImage.setXmin(0) rawImage.setXmax(self.imageFile.width) rawImage.renderHdr() self.frame.setImage(rawImage) return def extractDoppler(self): ''' Evaluate the doppler polynomial and return the average value for now. ''' midwidth = self.frame.getNumberOfSamples() / 2.0 dop = 0.0 prod = 1.0 for ind, kk in enumerate(self.doppler_coeff): dop += kk * prod prod *= midwidth print ('Average Doppler: {0}'.format(dop)) ####For insarApp quadratic = {} quadratic['a'] = dop / self.frame.getInstrument().getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. ####For roiApp ####More accurate ####CEOS already provides function vs pixel self.frame._dopplerVsPixel = self.doppler_coeff return quadratic def _decodeSceneReferenceNumber(self,referenceNumber): return referenceNumber
class ERS_SLC(Sensor): family = 'ers_slc' logging_name = 'isce.sensor.ers_slc' parameter_list = (IMAGEFILE, LEADERFILE, ORBIT_TYPE, ORBIT_DIRECTORY, ORBIT_FILE) + Sensor.parameter_list @logged def __init__(self, name=''): super().__init__(family=self.__class__.family, name=name) self.frame = Frame() self.frame.configure() self.dopplerRangeTime = None # Constants are from # J. J. Mohr and S. N. Madsen. Geometric calibration of ERS satellite # SAR images. IEEE T. Geosci. Remote, 39(4):842-850, Apr. 2001. self.constants = {'polarization': 'VV', 'antennaLength': 10, 'lookDirection': 'RIGHT', 'chirpPulseBandwidth': 15.50829e6, 'rangeSamplingRate': 18.962468e6, 'delayTime':6.622e-6, 'iBias': 15.5, 'qBias': 15.5} return None def getFrame(self): return self.frame def parse(self): self.leaderFile = LeaderFile(file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(self) self.imageFile.parse() self.populateMetadata() def populateMetadata(self): """ Create the appropriate metadata objects from our CEOSFormat metadata """ self._populatePlatform() self._populateInstrument() self._populateFrame() if (self._orbitType == 'ODR'): self._populateDelftOrbits() elif (self._orbitType == 'PRC'): self._populatePRCOrbits() elif (self._orbitType == 'PDS'): self._populatePDSOrbits() else: self._populateHeaderOrbit() self._populateDoppler() def _populatePlatform(self): """ Populate the platform object with metadata """ platform = self.frame.getInstrument().getPlatform() platform.setMission(self.leaderFile.sceneHeaderRecord.metadata[ 'Sensor platform mission identifier']) platform.setAntennaLength(self.constants['antennaLength']) platform.setPointingDirection(-1) platform.setPlanet(Planet(pname='Earth')) def _populateInstrument(self): """Populate the instrument object with metadata""" instrument = self.frame.getInstrument() prf = self.leaderFile.sceneHeaderRecord.metadata['Pulse Repetition Frequency'] rangeSamplingRate = self.leaderFile.sceneHeaderRecord.metadata['Range sampling rate']*1.0e6 rangePixelSize = Const.c/(2.0*rangeSamplingRate) instrument.setRadarWavelength( self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength']) instrument.setIncidenceAngle( self.leaderFile.sceneHeaderRecord.metadata[ 'Incidence angle at scene centre']) instrument.setPulseRepetitionFrequency(prf) instrument.setRangeSamplingRate(rangeSamplingRate) instrument.setRangePixelSize(rangePixelSize) instrument.setPulseLength(self.leaderFile.sceneHeaderRecord.metadata[ 'Range pulse length']*1e-6) instrument.setChirpSlope(self.constants['chirpPulseBandwidth']/ (self.leaderFile.sceneHeaderRecord.metadata['Range pulse length']* 1e-6)) instrument.setInPhaseValue(self.constants['iBias']) instrument.setQuadratureValue(self.constants['qBias']) def _populateFrame(self): """Populate the scene object with metadata""" rangeSamplingRate = self.constants['rangeSamplingRate'] rangePixelSize = Const.c/(2.0*rangeSamplingRate) pulseInterval = 1.0/self.frame.getInstrument().getPulseRepetitionFrequency() frame = self._decodeSceneReferenceNumber( self.leaderFile.sceneHeaderRecord.metadata[ 'Scene reference number']) prf = self.frame.instrument.getPulseRepetitionFrequency() tau0 = self.leaderFile.sceneHeaderRecord.metadata['Zero-doppler range time of first range pixel']*1.0e-3 startingRange = tau0*Const.c/2.0 farRange = startingRange + self.imageFile.width*rangePixelSize first_line_utc = datetime.datetime.strptime(self.leaderFile.sceneHeaderRecord.metadata['Zero-doppler azimuth time of first azimuth pixel'], "%d-%b-%Y %H:%M:%S.%f") mid_line_utc = first_line_utc + datetime.timedelta(seconds = (self.imageFile.length-1) * 0.5 / prf) last_line_utc = first_line_utc + datetime.timedelta(seconds = (self.imageFile.length-1)/prf) self.logger.debug("Frame UTC start, mid, end times: %s %s %s" % (first_line_utc,mid_line_utc,last_line_utc)) self.frame.setFrameNumber(frame) self.frame.setOrbitNumber(self.leaderFile.sceneHeaderRecord.metadata['Orbit number']) self.frame.setStartingRange(startingRange) self.frame.setFarRange(farRange) self.frame.setProcessingFacility(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier']) self.frame.setProcessingSystem(self.leaderFile.sceneHeaderRecord.metadata['Processing system identifier']) self.frame.setProcessingSoftwareVersion(self.leaderFile.sceneHeaderRecord.metadata['Processing version identifier']) self.frame.setPolarization(self.constants['polarization']) self.frame.setNumberOfLines(self.imageFile.length) self.frame.setNumberOfSamples(self.imageFile.width) self.frame.setSensingStart(first_line_utc) self.frame.setSensingMid(mid_line_utc) self.frame.setSensingStop(last_line_utc) def _populateHeaderOrbit(self): """Populate an orbit object with the header orbits""" self.logger.info("Using Header Orbits") orbit = self.frame.getOrbit() orbit.setOrbitSource('Header') orbit.setOrbitQuality('Unknown') t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord.metadata['Year of data point'], month=self.leaderFile.platformPositionRecord.metadata['Month of data point'], day=self.leaderFile.platformPositionRecord.metadata['Day of data point']) t0 = t0 + datetime.timedelta(microseconds=self.leaderFile.platformPositionRecord.metadata['Seconds of day']*1e6) for i in range(self.leaderFile.platformPositionRecord.metadata['Number of data points']): vec = StateVector() deltaT = self.leaderFile.platformPositionRecord.metadata['Time interval between DATA points'] t = t0 + datetime.timedelta(microseconds=i*deltaT*1e6) vec.setTime(t) dataPoints = self.leaderFile.platformPositionRecord.metadata['Positional Data Points'][i] vec.setPosition([dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z']]) vec.setVelocity([dataPoints['Velocity vector X'], dataPoints['Velocity vector Y'], dataPoints['Velocity vector Z']]) orbit.addStateVector(vec) def _populateDelftOrbits(self): """Populate an orbit object with the Delft orbits""" from isceobj.Orbit.ODR import ODR, Arclist self.logger.info("Using Delft Orbits") arclist = Arclist(os.path.join(self._orbitDir,'arclist')) arclist.parse() orbitFile = arclist.getOrbitFile(self.frame.getSensingStart()) odr = ODR(file=os.path.join(self._orbitDir,orbitFile)) startTimePreInterp = self.frame.getSensingStart() - datetime.timedelta(minutes=60) stopTimePreInterp = self.frame.getSensingStop() + datetime.timedelta(minutes=60) odr.parseHeader(startTimePreInterp,stopTimePreInterp) startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) orbit = odr.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def _populatePRCOrbits(self): """Populate an orbit object the D-PAF PRC orbits""" from isceobj.Orbit.PRC import PRC, Arclist self.logger.info("Using PRC Orbits") arclist = Arclist(os.path.join(self._orbitDir,'arclist')) arclist.parse() orbitFile = arclist.getOrbitFile(self.frame.getSensingStart()) self.logger.debug("Using file %s" % (orbitFile)) prc = PRC(file=os.path.join(self._orbitDir,orbitFile)) prc.parse() startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) fullOrbit = prc.getOrbit() orbit = fullOrbit.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def _populatePDSOrbits(self): """ Populate an orbit object using the ERS-2 PDS format """ from isceobj.Orbit.PDS import PDS self.logger.info("Using PDS Orbits") pds = PDS(file=self._orbitFile) pds.parse() startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) fullOrbit = pds.getOrbit() orbit = fullOrbit.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def _populateDoppler(self): ''' Extract doppler from the CEOS file. ''' prf = self.frame.instrument.getPulseRepetitionFrequency() #####ERS provides doppler as a function of slant range time in seconds d0 = self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid constant term'] d1 = self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid linear term'] d2 = self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid quadratic term'] self.dopplerRangeTime = [d0, d1, d2] return def extractDoppler(self): width = self.frame.getNumberOfSamples() prf = self.frame.instrument.getPulseRepetitionFrequency() midtime = 0.5*width/self.frame.instrument.getRangeSamplingRate() fd_mid = 0.0 x = 1.0 for ind, coeff in enumerate(self.dopplerRangeTime): fd_mid += coeff * x x *= midtime ####For insarApp quadratic = {} quadratic['a'] = fd_mid / prf quadratic['b'] = 0.0 quadratic['c'] = 0.0 ###For roiApp more accurate ####Convert stuff to pixel wise coefficients dr = self.frame.getInstrument().getRangePixelSize() norm = 0.5*Const.c/dr dcoeffs = [] for ind, val in enumerate(self.dopplerRangeTime): dcoeffs.append( val / (norm**ind)) self.frame._dopplerVsPixel = dcoeffs print('Doppler Fit: ', fit[::-1]) return quadratic def extractImage(self): import array import math self.parse() try: out = open(self.output, 'wb') except: raise Exception('Cannot open output file: %s'%(self.output)) self.imageFile.extractImage(output=out) out.close() rawImage = isceobj.createSlcImage() rawImage.setByteOrder('l') rawImage.setAccessMode('read') rawImage.setFilename(self.output) rawImage.setWidth(self.imageFile.width) rawImage.setXmin(0) rawImage.setXmax(self.imageFile.width) self.frame.setImage(rawImage) prf = self.frame.getInstrument().getPulseRepetitionFrequency() senStart = self.frame.getSensingStart() numPulses = int(math.ceil(DTU.timeDeltaToSeconds(self.frame.getSensingStop()-senStart)*prf)) musec0 = (senStart.hour*3600 + senStart.minute*60 + senStart.second)*10**6 + senStart.microsecond maxMusec = (24*3600)*10**6#use it to check if we went across a day. very rare day0 = (datetime.datetime(senStart.year,senStart.month,senStart.day) - datetime.datetime(senStart.year,1,1)).days + 1 outputArray = array.array('d',[0]*2*numPulses) self.frame.auxFile = self.output + '.aux' fp = open(self.frame.auxFile,'wb') j = -1 for i1 in range(numPulses): j += 1 musec = round((j/prf)*10**6) + musec0 if musec >= maxMusec: day0 += 1 musec0 = musec%maxMusec musec = musec0 j = 0 outputArray[2*i1] = day0 outputArray[2*i1+1] = musec outputArray.tofile(fp) fp.close() def _decodeSceneReferenceNumber(self,referenceNumber): frameNumber = referenceNumber.split('=') if (len(frameNumber) > 2): frameNumber = frameNumber[2].strip() else: frameNumber = frameNumber[0] return frameNumber
class COSMO_SkyMed_SLC(Sensor): """ A class representing a Level1Product meta data. Level1Product(hdf5=h5filename) will parse the hdf5 file and produce an object with attributes for metadata. """ parameter_list = (HDF5, ) + Sensor.parameter_list logging_name = 'isce.Sensor.COSMO_SkyMed_SLC' family = 'cosmo_skymed_slc' def __init__(self, family='', name=''): super(COSMO_SkyMed_SLC, self).__init__(family if family else self.__class__.family, name=name) self.frame = Frame() self.frame.configure() # Some extra processing parameters unique to CSK SLC (currently) self.dopplerRangeTime = [] self.dopplerAzimuthTime = [] self.azimuthRefTime = None self.rangeRefTime = None self.rangeFirstTime = None self.rangeLastTime = None self.lookMap = {'RIGHT': -1, 'LEFT': 1} return def __getstate__(self): d = dict(self.__dict__) del d['logger'] return d def __setstate__(self, d): self.__dict__.update(d) self.logger = logging.getLogger('isce.Sensor.COSMO_SkyMed_SLC') return def getFrame(self): return self.frame def parse(self): try: fp = h5py.File(self.hdf5, 'r') except Exception as strerr: self.logger.error("IOError: %s" % strerr) return None self.populateMetadata(fp) fp.close() def populateMetadata(self, file): """ Populate our Metadata objects """ self._populatePlatform(file) self._populateInstrument(file) self._populateFrame(file) self._populateOrbit(file) self._populateExtras(file) def _populatePlatform(self, file): platform = self.frame.getInstrument().getPlatform() platform.setMission(file.attrs['Satellite ID']) platform.setPointingDirection( self.lookMap[file.attrs['Look Side'].decode('utf-8')]) platform.setPlanet(Planet(pname="Earth")) ####This is an approximation for spotlight mode ####In spotlight mode, antenna length changes with azimuth position platform.setAntennaLength(file.attrs['Antenna Length']) try: if file.attrs['Multi-Beam ID'].startswith('ES'): platform.setAntennaLength( 16000.0 / file['S01/SBI'].attrs['Line Time Interval']) except: pass def _populateInstrument(self, file): instrument = self.frame.getInstrument() # rangePixelSize = Const.c/(2*file['S01'].attrs['Sampling Rate']) rangePixelSize = file['S01/SBI'].attrs['Column Spacing'] instrument.setRadarWavelength(file.attrs['Radar Wavelength']) # instrument.setPulseRepetitionFrequency(file['S01'].attrs['PRF']) instrument.setPulseRepetitionFrequency( 1.0 / file['S01/SBI'].attrs['Line Time Interval']) instrument.setRangePixelSize(rangePixelSize) instrument.setPulseLength(file['S01'].attrs['Range Chirp Length']) instrument.setChirpSlope(file['S01'].attrs['Range Chirp Rate']) # instrument.setRangeSamplingRate(file['S01'].attrs['Sampling Rate']) instrument.setRangeSamplingRate( 1.0 / file['S01/SBI'].attrs['Column Time Interval']) incangle = 0.5 * (file['S01/SBI'].attrs['Far Incidence Angle'] + file['S01/SBI'].attrs['Near Incidence Angle']) instrument.setIncidenceAngle(incangle) def _populateFrame(self, file): rft = file['S01/SBI'].attrs['Zero Doppler Range First Time'] slantRange = rft * Const.c / 2.0 self.frame.setStartingRange(slantRange) referenceUTC = self._parseNanoSecondTimeStamp( file.attrs['Reference UTC']) relStart = file['S01/SBI'].attrs['Zero Doppler Azimuth First Time'] relEnd = file['S01/SBI'].attrs['Zero Doppler Azimuth Last Time'] relMid = 0.5 * (relStart + relEnd) sensingStart = self._combineDateTime(referenceUTC, relStart) sensingStop = self._combineDateTime(referenceUTC, relEnd) sensingMid = self._combineDateTime(referenceUTC, relMid) self.frame.setPassDirection(file.attrs['Orbit Direction']) self.frame.setOrbitNumber(file.attrs['Orbit Number']) self.frame.setProcessingFacility(file.attrs['Processing Centre']) self.frame.setProcessingSoftwareVersion( file.attrs['L0 Software Version']) self.frame.setPolarization(file['S01'].attrs['Polarisation']) self.frame.setNumberOfLines(file['S01/SBI'].shape[0]) self.frame.setNumberOfSamples(file['S01/SBI'].shape[1]) self.frame.setSensingStart(sensingStart) self.frame.setSensingMid(sensingMid) self.frame.setSensingStop(sensingStop) rangePixelSize = self.frame.getInstrument().getRangePixelSize() farRange = slantRange + (self.frame.getNumberOfSamples() - 1) * rangePixelSize self.frame.setFarRange(farRange) def _populateOrbit(self, file): orbit = self.frame.getOrbit() orbit.setReferenceFrame('ECR') orbit.setOrbitSource('Header') t0 = datetime.datetime.strptime( file.attrs['Reference UTC'].decode('utf-8'), '%Y-%m-%d %H:%M:%S.%f000') t = file.attrs['State Vectors Times'] position = file.attrs['ECEF Satellite Position'] velocity = file.attrs['ECEF Satellite Velocity'] for i in range(len(position)): vec = StateVector() dt = t0 + datetime.timedelta(seconds=t[i]) vec.setTime(dt) vec.setPosition([position[i, 0], position[i, 1], position[i, 2]]) vec.setVelocity([velocity[i, 0], velocity[i, 1], velocity[i, 2]]) orbit.addStateVector(vec) def _populateExtras(self, file): """ Populate some of the extra fields unique to processing TSX data. In the future, other sensors may need this information as well, and a re-organization may be necessary. """ from isceobj.Doppler.Doppler import Doppler self.dopplerRangeTime = file.attrs['Centroid vs Range Time Polynomial'] self.dopplerAzimuthTime = file.attrs[ 'Centroid vs Azimuth Time Polynomial'] self.rangeRefTime = file.attrs['Range Polynomial Reference Time'] self.azimuthRefTime = file.attrs['Azimuth Polynomial Reference Time'] self.rangeFirstTime = file['S01/SBI'].attrs[ 'Zero Doppler Range First Time'] self.rangeLastTime = file['S01/SBI'].attrs[ 'Zero Doppler Range Last Time'] # get Doppler rate information, vs. azimuth first EJF 2015/00/05 # guessing that same scale applies as for Doppler centroid self.dopplerRateCoeffs = file.attrs[ 'Doppler Rate vs Azimuth Time Polynomial'] def extractImage(self): import os from ctypes import cdll, c_char_p extract_csk = cdll.LoadLibrary(os.path.dirname(__file__) + '/csk.so') inFile_c = c_char_p(bytes(self.hdf5, 'utf-8')) outFile_c = c_char_p(bytes(self.output, 'utf-8')) extract_csk.extract_csk_slc(inFile_c, outFile_c) self.parse() slcImage = isceobj.createSlcImage() slcImage.setFilename(self.output) slcImage.setXmin(0) slcImage.setXmax(self.frame.getNumberOfSamples()) slcImage.setWidth(self.frame.getNumberOfSamples()) slcImage.setAccessMode('r') self.frame.setImage(slcImage) def _parseNanoSecondTimeStamp(self, timestamp): """ Parse a date-time string with nanosecond precision and return a datetime object """ dateTime, nanoSeconds = timestamp.decode('utf-8').split('.') microsec = float(nanoSeconds) * 1e-3 dt = datetime.datetime.strptime(dateTime, '%Y-%m-%d %H:%M:%S') dt = dt + datetime.timedelta(microseconds=microsec) return dt def _combineDateTime(self, dobj, secsstr): '''Takes the date from dobj and time from secs to spit out a date time object. ''' sec = float(secsstr) dt = datetime.timedelta(seconds=sec) return datetime.datetime.combine(dobj.date(), datetime.time(0, 0)) + dt def extractDoppler(self): """ Return the doppler centroid as defined in the HDF5 file. """ import numpy as np quadratic = {} midtime = (self.rangeLastTime + self.rangeFirstTime) * 0.5 - self.rangeRefTime fd_mid = 0.0 x = 1.0 for ind, coeff in enumerate(self.dopplerRangeTime): fd_mid += coeff * x x *= midtime ####insarApp style quadratic['a'] = fd_mid / self.frame.getInstrument( ).getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. ####For roiApp more accurate ####Convert stuff to pixel wise coefficients from isceobj.Util import Poly1D coeffs = self.dopplerRangeTime dr = self.frame.getInstrument().getRangePixelSize() rref = 0.5 * Const.c * self.rangeRefTime r0 = self.frame.getStartingRange() norm = 0.5 * Const.c / dr dcoeffs = [] for ind, val in enumerate(coeffs): dcoeffs.append(val / (norm**ind)) poly = Poly1D.Poly1D() poly.initPoly(order=len(coeffs) - 1) poly.setMean((rref - r0) / dr - 1.0) poly.setCoeffs(dcoeffs) pix = np.linspace(0, self.frame.getNumberOfSamples(), num=len(coeffs) + 1) evals = poly(pix) fit = np.polyfit(pix, evals, len(coeffs) - 1) self.frame._dopplerVsPixel = list(fit[::-1]) print('Doppler Fit: ', fit[::-1]) #EMG - 20160420 This section was introduced in the populateMetadata method by EJF in r2022 #Its pupose seems to be to set self.doppler_coeff and self.azfmrate_coeff, which don't seem #to be used anywhere in ISCE. Need to take time to understand the need for this and consult #with EJF. # ## save the Doppler centroid coefficients, converting units from .h5 file ## units in the file are quadratic coefficients in Hz, Hz/sec, and Hz/(sec^2) ## ISCE expects Hz, Hz/(range sample), Hz/(range sample)^2 ## note that RS2 Doppler values are estimated at time dc.dopplerCentroidReferenceTime, ## so the values might need to be adjusted for ISCE usage ## adapted from RS2 version EJF 2015/09/05 # poly = self.frame._dopplerVsPixel # rangeSamplingRate = self.frame.getInstrument().getPulseRepetitionFrequency() # # need to convert units # poly[1] = poly[1]/rangeSamplingRate # poly[2] = poly[2]/rangeSamplingRate**2 # self.doppler_coeff = poly # ## similarly save Doppler azimuth fm rate values, converting units ## units in the file are quadratic coefficients in Hz, Hz/sec, and Hz/(sec^2) ## units are already converted below ## Guessing that ISCE expects Hz, Hz/(azimuth line), Hz/(azimuth line)^2 ## note that RS2 Doppler values are estimated at time dc.dopplerRateReferenceTime, ## so the values might need to be adjusted for ISCE usage ## modified from RS2 version EJF 2015/09/05 ## CSK Doppler azimuth FM rate not yet implemented in reading section, set to zero for now # # fmpoly = self.dopplerRateCoeffs # # don't need to convert units ## fmpoly[1] = fmpoly[1]/rangeSamplingRate ## fmpoly[2] = fmpoly[2]/rangeSamplingRate**2 # self.azfmrate_coeff = fmpoly #EMG - 20160420 return quadratic
class Radarsat2(Component): """ A Class representing RadarSAT 2 data """ def __init__(self): Component.__init__(self) self.xml = None self.tiff = None self.output = None self.product = _Product() self.frame = Frame() self.frame.configure() self.descriptionOfVariables = {} self.dictionaryOfVariables = {'XML': ['self.xml','str','mandatory'], 'TIFF': ['self.tiff','str','mandatory'], 'OUTPUT': ['self.output','str','optional']} def getFrame(self): return self.frame def parse(self): try: fp = open(self.xml,'r') except IOError as strerr: print("IOError: %s" % strerr) return self._xml_root = ElementTree(file=fp).getroot() self.product.set_from_etnode(self._xml_root) self.populateMetadata() fp.close() def populateMetadata(self): """ Create metadata objects from the metadata files """ mission = self.product.sourceAttributes.satellite swath = self.product.sourceAttributes.radarParameters.beams frequency = self.product.sourceAttributes.radarParameters.radarCenterFrequency prf = self.product.sourceAttributes.radarParameters.prf rangePixelSize = self.product.imageAttributes.rasterAttributes.sampledPixelSpacing rangeSamplingRate = Const.c/(2*rangePixelSize) pulseLength = self.product.sourceAttributes.radarParameters.pulseLengths[0] pulseBandwidth = self.product.sourceAttributes.radarParameters.pulseBandwidths[0] polarization = self.product.sourceAttributes.radarParameters.polarizations lookSide = lookMap[self.product.sourceAttributes.radarParameters.antennaPointing.upper()] facility = self.product.imageGenerationParameters.generalProcessingInformation._processingFacility version = self.product.imageGenerationParameters.generalProcessingInformation.softwareVersion lines = self.product.imageAttributes.rasterAttributes.numberOfLines samples = self.product.imageAttributes.rasterAttributes.numberOfSamplesPerLine startingRange = self.product.imageGenerationParameters.slantRangeToGroundRange.slantRangeTimeToFirstRangeSample * (Const.c/2) incidenceAngle = (self.product.imageGenerationParameters.sarProcessingInformation.incidenceAngleNearRange + self.product.imageGenerationParameters.sarProcessingInformation.incidenceAngleFarRange)/2 lineFlip = (self.product.imageAttributes.rasterAttributes.lineTimeOrdering.upper() == 'DECREASING') if lineFlip: dataStopTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeFirstLine dataStartTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeLastLine else: dataStartTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeFirstLine dataStopTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeLastLine passDirection = self.product.sourceAttributes.orbitAndAttitude.orbitInformation.passDirection height = self.product.imageGenerationParameters.sarProcessingInformation._satelliteHeight ####Populate platform platform = self.frame.getInstrument().getPlatform() platform.setPlanet(Planet("Earth")) platform.setMission(mission) platform.setPointingDirection(lookSide) platform.setAntennaLength(15.0) ####Populate instrument instrument = self.frame.getInstrument() instrument.setRadarFrequency(frequency) instrument.setPulseRepetitionFrequency(prf) instrument.setPulseLength(pulseLength) instrument.setChirpSlope(pulseBandwidth/pulseLength) instrument.setIncidenceAngle(incidenceAngle) #self.frame.getInstrument().setRangeBias(0) instrument.setRangePixelSize(rangePixelSize) instrument.setRangeSamplingRate(rangeSamplingRate) instrument.setBeamNumber(swath) instrument.setPulseLength(pulseLength) #Populate Frame #self.frame.setSatelliteHeight(height) self.frame.setSensingStart(dataStartTime) self.frame.setSensingStop(dataStopTime) diffTime = DTUtil.timeDeltaToSeconds(dataStopTime - dataStartTime)/2.0 sensingMid = dataStartTime + datetime.timedelta(microseconds=int(diffTime*1e6)) self.frame.setSensingMid(sensingMid) self.frame.setPassDirection(passDirection) self.frame.setPolarization(polarization) self.frame.setStartingRange(startingRange) self.frame.setFarRange(startingRange + (samples-1)*rangePixelSize) self.frame.setNumberOfLines(lines) self.frame.setNumberOfSamples(samples) self.frame.setProcessingFacility(facility) self.frame.setProcessingSoftwareVersion(version) # Initialize orbit objects # Read into temp orbit first. # Radarsat 2 needs orbit extensions. tempOrbit = Orbit() self.frame.getOrbit().setOrbitSource('Header: ' + self.product.sourceAttributes.orbitAndAttitude.orbitInformation.orbitDataFile) self.frame.setPassDirection(passDirection) stateVectors = self.product.sourceAttributes.orbitAndAttitude.orbitInformation.stateVectors for i in range(len(stateVectors)): position = [stateVectors[i].xPosition, stateVectors[i].yPosition, stateVectors[i].zPosition] velocity = [stateVectors[i].xVelocity, stateVectors[i].yVelocity, stateVectors[i].zVelocity] vec = StateVector() vec.setTime(stateVectors[i].timeStamp) vec.setPosition(position) vec.setVelocity(velocity) tempOrbit.addStateVector(vec) planet = self.frame.instrument.platform.planet orbExt = OrbitExtender(planet=planet) orbExt.configure() newOrb = orbExt.extendOrbit(tempOrbit) for sv in newOrb: self.frame.getOrbit().addStateVector(sv) def extractImage(self, verbose=True): ''' Use gdal to extract the slc. ''' try: from osgeo import gdal except ImportError: raise Exception('GDAL python bindings not found. Need this for RSAT2 / TandemX / Sentinel1A.') self.parse() width = self.frame.getNumberOfSamples() lgth = self.frame.getNumberOfLines() lineFlip = (self.product.imageAttributes.rasterAttributes.lineTimeOrdering.upper() == 'DECREASING') pixFlip = (self.product.imageAttributes.rasterAttributes.pixelTimeOrdering.upper() == 'DECREASING') src = gdal.Open(self.tiff.strip(), gdal.GA_ReadOnly) cJ = np.complex64(1.0j) ####Images are small enough that we can do it all in one go - Piyush real = src.GetRasterBand(1).ReadAsArray(0,0,width,lgth) imag = src.GetRasterBand(2).ReadAsArray(0,0,width,lgth) if (real is None) or (imag is None): raise Exception('Input Radarsat2 SLC seems to not be a 2 band Int16 image.') data = real+cJ*imag real = None imag = None src = None if lineFlip: if verbose: print('Vertically Flipping data') data = np.flipud(data) if pixFlip: if verbose: print('Horizontally Flipping data') data = np.fliplr(data) data.tofile(self.output) #### slcImage = isceobj.createSlcImage() slcImage.setByteOrder('l') slcImage.setFilename(self.output) slcImage.setAccessMode('read') slcImage.setWidth(width) slcImage.setLength(lgth) slcImage.setXmin(0) slcImage.setXmax(width) # slcImage.renderHdr() self.frame.setImage(slcImage) def extractDoppler(self): ''' self.parse() Extract doppler information as needed by mocomp ''' ins = self.frame.getInstrument() dc = self.product.imageGenerationParameters.dopplerCentroid quadratic = {} r0 = self.frame.startingRange fs = ins.getRangeSamplingRate() tNear = 2*r0/Const.c tMid = tNear + 0.5*self.frame.getNumberOfSamples()/fs t0 = dc.dopplerCentroidReferenceTime poly = dc.dopplerCentroidCoefficients fd_mid = 0.0 for kk in range(len(poly)): fd_mid += poly[kk] * (tMid - t0)**kk quadratic['a'] = fd_mid / ins.getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. return quadratic
class Sentinel1A(Component): """ A Class representing RadarSAT 2 data """ def __init__(self): Component.__init__(self) self.xml = None self.tiff = None self.orbitfile = None self.output = None self.frame = Frame() self.frame.configure() self._xml_root = None self.descriptionOfVariables = {} self.dictionaryOfVariables = { 'XML': ['self.xml', 'str', 'mandatory'], 'TIFF': ['self.tiff', 'str', 'mandatory'], 'ORBITFILE': ['self.orbitfile', 'str', 'optional'], 'OUTPUT': ['self.output', 'str', 'optional'] } def getFrame(self): return self.frame def parse(self): try: fp = open(self.xml, 'r') except IOError as strerr: print("IOError: %s" % strerr) return self._xml_root = ElementTree(file=fp).getroot() # self.product.set_from_etnode(self._xml_root) self.populateMetadata() fp.close() def grab_from_xml(self, path): try: res = self._xml_root.find(path).text except: raise Exception('Tag= %s not found' % (path)) if res is None: raise Exception('Tag = %s not found' % (path)) return res def convertToDateTime(self, string): dt = datetime.datetime.strptime(string, "%Y-%m-%dT%H:%M:%S.%f") return dt def populateMetadata(self): """ Create metadata objects from the metadata files """ ####Set each parameter one - by - one mission = self.grab_from_xml('adsHeader/missionId') swath = self.grab_from_xml('adsHeader/swath') polarization = self.grab_from_xml('adsHeader/polarisation') frequency = float( self.grab_from_xml( 'generalAnnotation/productInformation/radarFrequency')) passDirection = self.grab_from_xml( 'generalAnnotation/productInformation/pass') rangePixelSize = float( self.grab_from_xml( 'imageAnnotation/imageInformation/rangePixelSpacing')) azimuthPixelSize = float( self.grab_from_xml( 'imageAnnotation/imageInformation/azimuthPixelSpacing')) rangeSamplingRate = Const.c / (2.0 * rangePixelSize) prf = 1.0 / float( self.grab_from_xml( 'imageAnnotation/imageInformation/azimuthTimeInterval')) lines = int( self.grab_from_xml( 'imageAnnotation/imageInformation/numberOfLines')) samples = int( self.grab_from_xml( 'imageAnnotation/imageInformation/numberOfSamples')) startingRange = float( self.grab_from_xml( 'imageAnnotation/imageInformation/slantRangeTime') ) * Const.c / 2.0 incidenceAngle = float( self.grab_from_xml( 'imageAnnotation/imageInformation/incidenceAngleMidSwath')) dataStartTime = self.convertToDateTime( self.grab_from_xml( 'imageAnnotation/imageInformation/productFirstLineUtcTime')) dataStopTime = self.convertToDateTime( self.grab_from_xml( 'imageAnnotation/imageInformation/productLastLineUtcTime')) pulseLength = float( self.grab_from_xml( 'generalAnnotation/downlinkInformationList/downlinkInformation/downlinkValues/txPulseLength' )) chirpSlope = float( self.grab_from_xml( 'generalAnnotation/downlinkInformationList/downlinkInformation/downlinkValues/txPulseRampRate' )) pulseBandwidth = pulseLength * chirpSlope ####Sentinel is always right looking lookSide = -1 facility = 'EU' version = '1.0' # height = self.product.imageGenerationParameters.sarProcessingInformation._satelliteHeight ####Populate platform platform = self.frame.getInstrument().getPlatform() platform.setPlanet(Planet(pname="Earth")) platform.setMission(mission) platform.setPointingDirection(lookSide) platform.setAntennaLength(2 * azimuthPixelSize) ####Populate instrument instrument = self.frame.getInstrument() instrument.setRadarFrequency(frequency) instrument.setPulseRepetitionFrequency(prf) instrument.setPulseLength(pulseLength) instrument.setChirpSlope(pulseBandwidth / pulseLength) instrument.setIncidenceAngle(incidenceAngle) #self.frame.getInstrument().setRangeBias(0) instrument.setRangePixelSize(rangePixelSize) instrument.setRangeSamplingRate(rangeSamplingRate) instrument.setBeamNumber(swath) instrument.setPulseLength(pulseLength) #Populate Frame #self.frame.setSatelliteHeight(height) self.frame.setSensingStart(dataStartTime) self.frame.setSensingStop(dataStopTime) diffTime = DTUtil.timeDeltaToSeconds(dataStopTime - dataStartTime) / 2.0 sensingMid = dataStartTime + datetime.timedelta( microseconds=int(diffTime * 1e6)) self.frame.setSensingMid(sensingMid) self.frame.setPassDirection(passDirection) self.frame.setPolarization(polarization) self.frame.setStartingRange(startingRange) self.frame.setFarRange(startingRange + (samples - 1) * rangePixelSize) self.frame.setNumberOfLines(lines) self.frame.setNumberOfSamples(samples) self.frame.setProcessingFacility(facility) self.frame.setProcessingSoftwareVersion(version) self.frame.setPassDirection(passDirection) ResOrbFlag = self.extractResOrbit() if ResOrbFlag == 0: print( "cannot find POD Restituted Orbit, using orbit coming along with SLC" ) self.extractOrbit() ###################################################################################### def extractResOrbit(self): #read ESA's POD Restituted Orbit by Cunren Liang, APR. 2, 2015. import pathlib useResOrbFlag = 0 ResOrbDir = os.environ.get('RESORB') if ResOrbDir != None: print("Trying to find POD Restituted Orbit...") #get start time and stop time of the SLC data from data xml file dataStartTime = self.convertToDateTime( self.grab_from_xml( 'imageAnnotation/imageInformation/productFirstLineUtcTime') ) dataStopTime = self.convertToDateTime( self.grab_from_xml( 'imageAnnotation/imageInformation/productLastLineUtcTime')) #RESORB has an orbit every 10 sec, extend the start and stop time by 50 sec. dataStartTimeExt = dataStartTime - datetime.timedelta(0, 50) dataStopTimeExt = dataStopTime + datetime.timedelta(0, 50) ########################### #deal with orbit directory ########################### orbList = pathlib.Path(ResOrbDir).glob('**/*.EOF') for orb in orbList: #save full path orb = str(orb) orbx = orb #get orbit file name orb = os.path.basename(os.path.normpath(orb)) #print("{0}".format(orb)) #get start and stop time of the orbit file orbStartTime = datetime.datetime.strptime( orb[42:57], "%Y%m%dT%H%M%S") orbStopTime = datetime.datetime.strptime( orb[58:73], "%Y%m%dT%H%M%S") #print("{0}, {1}".format(orbStartTime, orbStopTime)) if dataStartTimeExt >= orbStartTime and dataStopTimeExt <= orbStopTime: try: orbfp = open(orbx, 'r') except IOError as strerr: print("IOError: %s" % strerr) return useResOrbFlag orbxml = ElementTree(file=orbfp).getroot() print('using orbit file: {0}'.format(orbx)) frameOrbit = Orbit() frameOrbit.setOrbitSource('Restituted') #find the orbit data from the file, and use them node = orbxml.find('Data_Block/List_of_OSVs' ) #note upper case and lower case for child in node.getchildren(): timestamp = self.convertToDateTime( child.find('UTC').text[4:]) if timestamp < dataStartTimeExt: continue if timestamp > dataStopTimeExt: break pos = [] vel = [] for tag in ['X', 'Y', 'Z']: pos.append(float(child.find(tag).text)) vel.append(float(child.find('V' + tag).text)) vec = StateVector() vec.setTime(timestamp) vec.setPosition(pos) vec.setVelocity(vel) frameOrbit.addStateVector(vec) #there is no need to extend the orbit any longer #planet = self.frame.instrument.platform.planet #orbExt = OrbitExtender(planet=planet) #orbExt.configure() #newOrb = orbExt.extendOrbit(frameOrbit) self.frame.getOrbit().setOrbitSource('Restituted') for sv in frameOrbit: self.frame.getOrbit().addStateVector(sv) orbfp.close() useResOrbFlag = 1 break return useResOrbFlag ###################################################################################### def extractOrbit(self): ''' Extract orbit information from xml node. ''' node = self._xml_root.find('generalAnnotation/orbitList') frameOrbit = Orbit() frameOrbit.setOrbitSource('Header') for child in node.getchildren(): timestamp = self.convertToDateTime(child.find('time').text) pos = [] vel = [] posnode = child.find('position') velnode = child.find('velocity') for tag in ['x', 'y', 'z']: pos.append(float(posnode.find(tag).text)) for tag in ['x', 'y', 'z']: vel.append(float(velnode.find(tag).text)) vec = StateVector() vec.setTime(timestamp) vec.setPosition(pos) vec.setVelocity(vel) frameOrbit.addStateVector(vec) planet = self.frame.instrument.platform.planet orbExt = OrbitExtender(planet=planet) orbExt.configure() newOrb = orbExt.extendOrbit(frameOrbit) self.frame.getOrbit().setOrbitSource('Header') for sv in newOrb: self.frame.getOrbit().addStateVector(sv) return def extractPreciseOrbit(self): ''' Extract precise orbit from given Orbit file. ''' try: fp = open(self.orbitfile, 'r') except IOError as strerr: print("IOError: %s" % strerr) return _xml_root = ElementTree(file=fp).getroot() node = _xml_root.find('Data_Block/List_of_OSVs') orb = Orbit() orb.configure() margin = datetime.timedelta(seconds=40.0) tstart = self.frame.getSensingStart() - margin tend = self.frame.getSensingStop() + margin for child in node.getchildren(): timestamp = self.convertToDateTime(child.find('UTC').text[4:]) if (timestamp >= tstart) and (timestamp < tend): pos = [] vel = [] for tag in ['VX', 'VY', 'VZ']: vel.append(float(child.find(tag).text)) for tag in ['X', 'Y', 'Z']: pos.append(float(child.find(tag).text)) vec = StateVector() vec.setTime(timestamp) vec.setPosition(pos) vec.setVelocity(vel) orb.addStateVector(vec) fp.close() self.frame.getOrbit().setOrbitSource('Header') for sv in orb: self.frame.getOrbit().addStateVector(sv) return def extractImage(self): """ Use gdal python bindings to extract image """ try: from osgeo import gdal except ImportError: raise Exception( 'GDAL python bindings not found. Need this for RSAT2/ TandemX / Sentinel1A.' ) self.parse() width = self.frame.getNumberOfSamples() lgth = self.frame.getNumberOfLines() src = gdal.Open(self.tiff.strip(), gdal.GA_ReadOnly) band = src.GetRasterBand(1) fid = open(self.output, 'wb') for ii in range(lgth): data = band.ReadAsArray(0, ii, width, 1) data.tofile(fid) fid.close() src = None band = None #### slcImage = isceobj.createSlcImage() slcImage.setByteOrder('l') slcImage.setFilename(self.output) slcImage.setAccessMode('read') slcImage.setWidth(self.frame.getNumberOfSamples()) slcImage.setLength(self.frame.getNumberOfLines()) slcImage.setXmin(0) slcImage.setXmax(self.frame.getNumberOfSamples()) self.frame.setImage(slcImage) def extractDoppler(self): ''' self.parse() Extract doppler information as needed by mocomp ''' # ins = self.frame.getInstrument() # dc = self.product.imageGenerationParameters.dopplerCentroid quadratic = {} # r0 = self.frame.startingRange # fs = ins.getRangeSamplingRate() # tNear = 2*r0/Const.c # tMid = tNear + 0.5*self.frame.getNumberOfSamples()/fs # t0 = dc.dopplerCentroidReferenceTime # poly = dc.dopplerCentroidCoefficients # fd_mid = 0.0 # for kk in range(len(poly)): # fd_mid += poly[kk] * (tMid - t0)**kk # quadratic['a'] = fd_mid / ins.getPulseRepetitionFrequency() quadratic['a'] = 0. quadratic['b'] = 0. quadratic['c'] = 0. return quadratic
class JERS(Component): """ Code to read CEOSFormat leader files for ERS-1/2 SAR data. The tables used to create this parser are based on document number ER-IS-EPO-GS-5902.1 from the European Space Agency. """ #Parsers.CEOS.CEOSFormat.ceosTypes['text'] = {'typeCode': 63, 'subtypeCode': [18,18,18]} #Parsers.CEOS.CEOSFormat.ceosTypes['leaderFile'] = {'typeCode': 192, 'subtypeCode': [63,18,18]} #Parsers.CEOS.CEOSFormat.ceosTypes['dataSetSummary'] = {'typeCode': 10, 'subtypeCode': [10,31,20]} #Parsers.CEOS.CEOSFormat.ceosTypes['platformPositionData'] = {'typeCode': 30, 'subtypeCode': [10,31,20]} #Parsers.CEOS.CEOSFormat.ceosTypes['facilityData'] = {'typeCode': 200, 'subtypeCode': [10,31,50]} #Parsers.CEOS.CEOSFormat.ceosTypes['datafileDescriptor'] = {'typeCode': 192, 'subtypeCode':[63,18,18]} #Parsers.CEOS.CEOSFormat.ceosTypes['signalData'] = {'typeCode': 10, 'subtypeCode': [50,31,20]} #Parsers.CEOS.CEOSFormat.ceosTypes['nullFileDescriptor'] = {'typeCode': 192, 'subtypeCode': [192,63,18]} def __init__(self): Component.__init__(self) self._leaderFile = None self._imageFile = None self.output = None self.frame = Frame() self.frame.configure() self.constants = {'polarization': 'HH', 'antennaLength': 12} self.descriptionOfVariables = {} self.dictionaryOfVariables = {'LEADERFILE': ['self._leaderFile','str','mandatory'], 'IMAGEFILE': ['self._imageFile','str','mandatory'], 'OUTPUT': ['self.output','str','optional']} def getFrame(self): return self.frame def parse(self): self.leaderFile = LeaderFile(file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(file=self._imageFile) self.imageFile.parse() self.populateMetadata() def populateMetadata(self): """ Create the appropriate metadata objects from our CEOSFormat metadata """ frame = self.leaderFile.sceneHeaderRecord.metadata['Scene reference number'].strip() frame = self._decodeSceneReferenceNumber(frame) rangePixelSize = Constants.SPEED_OF_LIGHT/(2*self.leaderFile.sceneHeaderRecord.metadata['Range sampling rate']*1e6) self.frame.getInstrument().getPlatform().setMission(self.leaderFile.sceneHeaderRecord.metadata['Sensor platform mission identifier']) self.frame.getInstrument().getPlatform().setPlanet(Planet(pname='Earth')) self.frame.getInstrument().setWavelength(self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength']) self.frame.getInstrument().setIncidenceAngle(self.leaderFile.sceneHeaderRecord.metadata['Incidence angle at scene centre']) self.frame.getInstrument().setPulseRepetitionFrequency(self.leaderFile.sceneHeaderRecord.metadata['Pulse Repetition Frequency']) self.frame.getInstrument().setRangePixelSize(rangePixelSize) self.frame.getInstrument().setPulseLength(self.leaderFile.sceneHeaderRecord.metadata['Range pulse length']*1e-6) chirpPulseBandwidth = 15.50829e6 # Is this really not in the CEOSFormat Header? self.frame.getInstrument().setChirpSlope(chirpPulseBandwidth/(self.leaderFile.sceneHeaderRecord.metadata['Range pulse length']*1e-6)) self.frame.setFrameNumber(frame) self.frame.setOrbitNumber(self.leaderFile.sceneHeaderRecord.metadata['Orbit number']) #self.frame.setStartingRange(self.leaderFile.facilityRecord.metadata['Slant range reference']) self.frame.setProcessingFacility(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier']) self.frame.setProcessingSystem(self.leaderFile.sceneHeaderRecord.metadata['Processing system identifier']) self.frame.setProcessingSoftwareVersion(self.leaderFile.sceneHeaderRecord.metadata['Processing version identifier']) self.frame.setPolarization('HH') self.frame.setNumberOfLines(self.imageFile.imageFDR.metadata['Number of lines per data set']) self.frame.setNumberOfSamples(self.imageFile.imageFDR.metadata['Number of pixels per line per SAR channel']) self.frame.getOrbit().setOrbitSource('Header') t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord.metadata['Year of data point'], month=self.leaderFile.platformPositionRecord.metadata['Month of data point'], day=self.leaderFile.platformPositionRecord.metadata['Day of data point']) t0 = t0 + datetime.timedelta(seconds=self.leaderFile.platformPositionRecord.metadata['Seconds of day']) for i in range(self.leaderFile.platformPositionRecord.metadata['Number of data points']): vec = StateVector() t = t0 + datetime.timedelta(seconds=(i*self.leaderFile.platformPositionRecord.metadata['Time interval between DATA points'])) vec.setTime(t) dataPoints = self.leaderFile.platformPositionRecord.metadata['Positional Data Points'][i] vec.setPosition([dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z']]) vec.setVelocity([dataPoints['Velocity vector X'], dataPoints['Velocity vector Y'], dataPoints['Velocity vector Z']]) self.frame.getOrbit().addStateVector(vec) def extractImage(self): raise NotImplementedError() def _decodeSceneReferenceNumber(self,referenceNumber): return referenceNumber
class Radarsat2(Sensor): """ A Class representing RADARSAT 2 data """ family = 'radarsat2' parameter_list = (XML, TIFF) + Sensor.parameter_list def __init__(self, family='', name=''): super().__init__(family if family else self.__class__.family, name=name) self.product = _Product() self.frame = Frame() self.frame.configure() def getFrame(self): return self.frame def parse(self): try: fp = open(self.xml, 'r') except IOError as strerr: print("IOError: %s" % strerr) return self._xml_root = ElementTree(file=fp).getroot() self.product.set_from_etnode(self._xml_root) self.populateMetadata() fp.close() def populateMetadata(self): """ Create metadata objects from the metadata files """ mission = self.product.sourceAttributes.satellite swath = self.product.sourceAttributes.radarParameters.beams frequency = self.product.sourceAttributes.radarParameters.radarCenterFrequency orig_prf = self.product.sourceAttributes.radarParameters.prf # original PRF not necessarily effective PRF rangePixelSize = self.product.imageAttributes.rasterAttributes.sampledPixelSpacing rangeSamplingRate = Const.c / (2 * rangePixelSize) pulseLength = self.product.sourceAttributes.radarParameters.pulseLengths[ 0] pulseBandwidth = self.product.sourceAttributes.radarParameters.pulseBandwidths[ 0] polarization = self.product.sourceAttributes.radarParameters.polarizations lookSide = lookMap[self.product.sourceAttributes.radarParameters. antennaPointing.upper()] facility = self.product.imageGenerationParameters.generalProcessingInformation._processingFacility version = self.product.imageGenerationParameters.generalProcessingInformation.softwareVersion lines = self.product.imageAttributes.rasterAttributes.numberOfLines samples = self.product.imageAttributes.rasterAttributes.numberOfSamplesPerLine startingRange = self.product.imageGenerationParameters.slantRangeToGroundRange.slantRangeTimeToFirstRangeSample * ( Const.c / 2) incidenceAngle = (self.product.imageGenerationParameters. sarProcessingInformation.incidenceAngleNearRange + self.product.imageGenerationParameters. sarProcessingInformation.incidenceAngleFarRange) / 2 # some RS2 scenes have oversampled SLC images because processed azimuth bandwidth larger than PRF EJF 2015/08/15 azimuthPixelSize = self.product.imageAttributes.rasterAttributes.sampledLineSpacing # ground spacing in meters totalProcessedAzimuthBandwidth = self.product.imageGenerationParameters.sarProcessingInformation.totalProcessedAzimuthBandwidth prf = orig_prf * np.ceil( totalProcessedAzimuthBandwidth / orig_prf ) # effective PRF can be double original, suggested by Piyush print("effective PRF %f, original PRF %f" % (prf, orig_prf)) lineFlip = (self.product.imageAttributes.rasterAttributes. lineTimeOrdering.upper() == 'DECREASING') if lineFlip: dataStopTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeFirstLine dataStartTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeLastLine else: dataStartTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeFirstLine dataStopTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeLastLine passDirection = self.product.sourceAttributes.orbitAndAttitude.orbitInformation.passDirection height = self.product.imageGenerationParameters.sarProcessingInformation._satelliteHeight ####Populate platform platform = self.frame.getInstrument().getPlatform() platform.setPlanet(Planet(pname="Earth")) platform.setMission(mission) platform.setPointingDirection(lookSide) platform.setAntennaLength(15.0) ####Populate instrument instrument = self.frame.getInstrument() instrument.setRadarFrequency(frequency) instrument.setPulseRepetitionFrequency(prf) instrument.setPulseLength(pulseLength) instrument.setChirpSlope(pulseBandwidth / pulseLength) instrument.setIncidenceAngle(incidenceAngle) #self.frame.getInstrument().setRangeBias(0) instrument.setRangePixelSize(rangePixelSize) instrument.setRangeSamplingRate(rangeSamplingRate) instrument.setBeamNumber(swath) instrument.setPulseLength(pulseLength) #Populate Frame #self.frame.setSatelliteHeight(height) self.frame.setSensingStart(dataStartTime) self.frame.setSensingStop(dataStopTime) diffTime = DTUtil.timeDeltaToSeconds(dataStopTime - dataStartTime) / 2.0 sensingMid = dataStartTime + datetime.timedelta( microseconds=int(diffTime * 1e6)) self.frame.setSensingMid(sensingMid) self.frame.setPassDirection(passDirection) self.frame.setPolarization(polarization) self.frame.setStartingRange(startingRange) self.frame.setFarRange(startingRange + (samples - 1) * rangePixelSize) self.frame.setNumberOfLines(lines) self.frame.setNumberOfSamples(samples) self.frame.setProcessingFacility(facility) self.frame.setProcessingSoftwareVersion(version) # Initialize orbit objects # Read into temp orbit first. # Radarsat 2 needs orbit extensions. tempOrbit = Orbit() self.frame.getOrbit().setOrbitSource( 'Header: ' + self.product.sourceAttributes.orbitAndAttitude. orbitInformation.orbitDataFile) self.frame.setPassDirection(passDirection) stateVectors = self.product.sourceAttributes.orbitAndAttitude.orbitInformation.stateVectors for i in range(len(stateVectors)): position = [ stateVectors[i].xPosition, stateVectors[i].yPosition, stateVectors[i].zPosition ] velocity = [ stateVectors[i].xVelocity, stateVectors[i].yVelocity, stateVectors[i].zVelocity ] vec = StateVector() vec.setTime(stateVectors[i].timeStamp) vec.setPosition(position) vec.setVelocity(velocity) tempOrbit.addStateVector(vec) planet = self.frame.instrument.platform.planet orbExt = OrbitExtender(planet=planet) orbExt.configure() newOrb = orbExt.extendOrbit(tempOrbit) for sv in newOrb: self.frame.getOrbit().addStateVector(sv) # save the Doppler centroid coefficients, converting units from product.xml file # units in the file are quadratic coefficients in Hz, Hz/sec, and Hz/(sec^2) # ISCE expects Hz, Hz/(range sample), Hz((range sample)^2 # note that RS2 Doppler values are estimated at time dc.dopplerCentroidReferenceTime, # so the values might need to be adjusted for ISCE usage # added EJF 2015/08/17 dc = self.product.imageGenerationParameters.dopplerCentroid poly = dc.dopplerCentroidCoefficients # need to convert units poly[1] = poly[1] / rangeSamplingRate poly[2] = poly[2] / rangeSamplingRate**2 self.doppler_coeff = poly # similarly save Doppler azimuth fm rate values, converting units # units in the file are quadratic coefficients in Hz, Hz/sec, and Hz/(sec^2) # Guessing that ISCE expects Hz, Hz/(range sample), Hz((range sample)^2 # note that RS2 Doppler values are estimated at time dc.dopplerRateReferenceTime, # so the values might need to be adjusted for ISCE usage # added EJF 2015/08/17 dr = self.product.imageGenerationParameters.dopplerRateValues fmpoly = dr.dopplerRateValuesCoefficients # need to convert units fmpoly[1] = fmpoly[1] / rangeSamplingRate fmpoly[2] = fmpoly[2] / rangeSamplingRate**2 self.azfmrate_coeff = fmpoly # now calculate effective PRF from the azimuth line spacing after we have the orbit info EJF 2015/08/15 # this does not work because azimuth spacing is on ground. Instead use bandwidth ratio calculated above EJF # SCHvelocity = self.frame.getSchVelocity() # SCHvelocity = 7550.75 # hard code orbit velocity for now m/s # prf = SCHvelocity/azimuthPixelSize # instrument.setPulseRepetitionFrequency(prf) def extractImage(self, verbose=True): ''' Use gdal to extract the slc. ''' try: from osgeo import gdal except ImportError: raise Exception( 'GDAL python bindings not found. Need this for RSAT2 / TandemX / Sentinel1A.' ) self.parse() width = self.frame.getNumberOfSamples() lgth = self.frame.getNumberOfLines() lineFlip = (self.product.imageAttributes.rasterAttributes. lineTimeOrdering.upper() == 'DECREASING') pixFlip = (self.product.imageAttributes.rasterAttributes. pixelTimeOrdering.upper() == 'DECREASING') src = gdal.Open(self.tiff.strip(), gdal.GA_ReadOnly) cJ = np.complex64(1.0j) ####Images are small enough that we can do it all in one go - Piyush real = src.GetRasterBand(1).ReadAsArray(0, 0, width, lgth) imag = src.GetRasterBand(2).ReadAsArray(0, 0, width, lgth) if (real is None) or (imag is None): raise Exception( 'Input Radarsat2 SLC seems to not be a 2 band Int16 image.') data = real + cJ * imag real = None imag = None src = None if lineFlip: if verbose: print('Vertically Flipping data') data = np.flipud(data) if pixFlip: if verbose: print('Horizontally Flipping data') data = np.fliplr(data) data.tofile(self.output) #### slcImage = isceobj.createSlcImage() slcImage.setByteOrder('l') slcImage.setFilename(self.output) slcImage.setAccessMode('read') slcImage.setWidth(width) slcImage.setLength(lgth) slcImage.setXmin(0) slcImage.setXmax(width) # slcImage.renderHdr() self.frame.setImage(slcImage) def extractDoppler(self): ''' self.parse() Extract doppler information as needed by mocomp ''' ins = self.frame.getInstrument() dc = self.product.imageGenerationParameters.dopplerCentroid quadratic = {} r0 = self.frame.startingRange fs = ins.getRangeSamplingRate() tNear = 2 * r0 / Const.c tMid = tNear + 0.5 * self.frame.getNumberOfSamples() / fs t0 = dc.dopplerCentroidReferenceTime poly = dc.dopplerCentroidCoefficients fd_mid = 0.0 for kk in range(len(poly)): fd_mid += poly[kk] * (tMid - t0)**kk ####For insarApp quadratic['a'] = fd_mid / ins.getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. ####For roiApp ####More accurate from isceobj.Util import Poly1D coeffs = poly dr = self.frame.getInstrument().getRangePixelSize() rref = 0.5 * Const.c * t0 r0 = self.frame.getStartingRange() norm = 0.5 * Const.c / dr dcoeffs = [] for ind, val in enumerate(coeffs): dcoeffs.append(val / (norm**ind)) poly = Poly1D.Poly1D() poly.initPoly(order=len(coeffs) - 1) poly.setMean((rref - r0) / dr - 1.0) poly.setCoeffs(dcoeffs) pix = np.linspace(0, self.frame.getNumberOfSamples(), num=len(coeffs) + 1) evals = poly(pix) fit = np.polyfit(pix, evals, len(coeffs) - 1) self.frame._dopplerVsPixel = list(fit[::-1]) print('Doppler Fit: ', fit[::-1]) return quadratic
class Radarsat1(Sensor): """ Code to read CEOSFormat leader files for Radarsat-1 SAR data. The tables used to create this parser are based on document number ER-IS-EPO-GS-5902.1 from the European Space Agency. """ family = 'radarsat1' logging_name = 'isce.sensor.radarsat1' parameter_list = (LEADERFILE, IMAGEFILE, PARFILE) + Sensor.parameter_list auxLength = 50 @logged def __init__(self, name=''): super().__init__(family=self.__class__.family, name=name) self.imageFile = None self.leaderFile = None #####Soecific doppler functions for RSAT1 self.doppler_ref_range = None self.doppler_ref_azi = None self.doppler_predict = None self.doppler_DAR = None self.doppler_coeff = None self.frame = Frame() self.frame.configure() self.constants = {'polarization': 'HH', 'antennaLength': 15} def getFrame(self): return self.frame def parse(self): self.leaderFile = LeaderFile(self, file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(self, file=self._imageFile) self.imageFile.parse() self.populateMetadata() if self._parFile: self.parseParFile() else: self.populateCEOSOrbit() def populateMetadata(self): """ Create the appropriate metadata objects from our CEOSFormat metadata """ frame = self._decodeSceneReferenceNumber( self.leaderFile.sceneHeaderRecord. metadata['Scene reference number']) try: rangePixelSize = Const.c / (2 * self.leaderFile.sceneHeaderRecord. metadata['Range sampling rate'] * 1e6) except ZeroDivisionError: rangePixelSize = 0 ins = self.frame.getInstrument() platform = ins.getPlatform() platform.setMission(self.leaderFile.sceneHeaderRecord. metadata['Sensor platform mission identifier']) platform.setAntennaLength(self.constants['antennaLength']) platform.setPointingDirection(-1) platform.setPlanet(Planet(pname='Earth')) ins.setRadarWavelength( self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength']) ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord. metadata['Incidence angle at scene centre']) ##RSAT-1 does not have PRF for raw data in leader file. # self.frame.getInstrument().setPulseRepetitionFrequency(self.leaderFile.sceneHeaderRecord.metadata['Pulse Repetition Frequency']) ins.setRangePixelSize(rangePixelSize) ins.setPulseLength( self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'] * 1e-6) chirpPulseBandwidth = 15.50829e6 # Is this really not in the CEOSFormat Header? ins.setChirpSlope( chirpPulseBandwidth / (self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'] * 1e-6)) ins.setInPhaseValue(7.5) ins.setQuadratureValue(7.5) self.frame.setFrameNumber(frame) self.frame.setOrbitNumber( self.leaderFile.sceneHeaderRecord.metadata['Orbit number']) self.frame.setProcessingFacility( self.leaderFile.sceneHeaderRecord. metadata['Processing facility identifier']) self.frame.setProcessingSystem( self.leaderFile.sceneHeaderRecord. metadata['Processing system identifier']) self.frame.setProcessingSoftwareVersion( self.leaderFile.sceneHeaderRecord. metadata['Processing version identifier']) self.frame.setPolarization(self.constants['polarization']) self.frame.setNumberOfLines( self.imageFile.imageFDR.metadata['Number of lines per data set']) self.frame.setNumberOfSamples( self.imageFile.imageFDR. metadata['Number of pixels per line per SAR channel']) self.frame.getOrbit().setOrbitSource('Header') self.frame.getOrbit().setOrbitQuality( self.leaderFile.platformPositionRecord. metadata['Orbital elements designator']) def populateCEOSOrbit(self): from isceobj.Orbit.Inertial import ECI2ECR t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord. metadata['Year of data point'], month=self.leaderFile.platformPositionRecord. metadata['Month of data point'], day=self.leaderFile.platformPositionRecord. metadata['Day of data point']) t0 = t0 + datetime.timedelta( seconds=self.leaderFile.platformPositionRecord. metadata['Seconds of day']) #####Read in orbit in inertial coordinates orb = Orbit() for i in range(self.leaderFile.platformPositionRecord. metadata['Number of data points']): vec = StateVector() t = t0 + datetime.timedelta( seconds=(i * self.leaderFile.platformPositionRecord. metadata['Time interval between DATA points'])) vec.setTime(t) dataPoints = self.leaderFile.platformPositionRecord.metadata[ 'Positional Data Points'][i] vec.setPosition([ dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z'] ]) vec.setVelocity([ dataPoints['Velocity vector X'] / 1000., dataPoints['Velocity vector Y'] / 1000., dataPoints['Velocity vector Z'] / 1000. ]) orb.addStateVector(vec) #####Convert orbits from ECI to ECEF frame. t0 = orb._stateVectors[0]._time ang = self.leaderFile.platformPositionRecord.metadata[ 'Greenwich mean hour angle'] cOrb = ECI2ECR(orb, GAST=ang, epoch=t0) wgsorb = cOrb.convert() orb = self.frame.getOrbit() for sv in wgsorb: orb.addStateVector(sv) print(sv) def extractImage(self): import isceobj if (self.imageFile is None) or (self.leaderFile is None): self.parse() try: out = open(self.output, 'wb') except IOError as strerr: self.logger.error("IOError: %s" % strerr) self.imageFile.extractImage(output=out) out.close() ####RSAT1 is weird. Contains all useful info in RAW data and not leader. ins = self.frame.getInstrument() ins.setPulseRepetitionFrequency(self.imageFile.prf) ins.setPulseLength(self.imageFile.pulseLength) ins.setRangeSamplingRate(self.imageFile.rangeSamplingRate) ins.setRangePixelSize(Const.c / (2 * self.imageFile.rangeSamplingRate)) ins.setChirpSlope(self.imageFile.chirpSlope) ###### self.frame.setSensingStart(self.imageFile.sensingStart) sensingStop = self.imageFile.sensingStart + datetime.timedelta( seconds=((self.frame.getNumberOfLines() - 1) / self.imageFile.prf)) sensingMid = self.imageFile.sensingStart + datetime.timedelta( seconds=0.5 * (sensingStop - self.imageFile.sensingStart).total_seconds()) self.frame.setSensingStop(sensingStop) self.frame.setSensingMid(sensingMid) self.frame.setNumberOfSamples(self.imageFile.width) self.frame.setStartingRange(self.imageFile.startingRange) farRange = self.imageFile.startingRange + ins.getRangePixelSize( ) * self.imageFile.width * 0.5 self.frame.setFarRange(farRange) rawImage = isceobj.createRawImage() rawImage.setByteOrder('l') rawImage.setAccessMode('read') rawImage.setFilename(self.output) rawImage.setWidth(self.imageFile.width) rawImage.setXmin(0) rawImage.setXmax(self.imageFile.width) rawImage.renderHdr() self.frame.setImage(rawImage) def parseParFile(self): '''Parse the par file if any is available.''' if self._parFile not in (None, ''): par = ParFile(self._parFile) ####Update orbit svs = par['prep_block']['sensor']['ephemeris']['sv_block'][ 'state_vector'] datefmt = '%Y%m%d%H%M%S%f' for entry in svs: sv = StateVector() sv.setPosition( [float(entry['x']), float(entry['y']), float(entry['z'])]) sv.setVelocity([ float(entry['xv']), float(entry['yv']), float(entry['zv']) ]) sv.setTime(datetime.datetime.strptime(entry['Date'], datefmt)) self.frame.orbit.addStateVector(sv) self.frame.orbit._stateVectors = sorted( self.frame.orbit._stateVectors, key=lambda x: x.getTime()) doppinfo = par['prep_block']['sensor']['beam'][ 'DopplerCentroidParameters'] #######Selectively update some values. #######Currently used only for doppler centroids. self.doppler_ref_range = float(doppinfo['reference_range']) self.doppler_ref_azi = datetime.datetime.strptime( doppinfo['reference_date'], '%Y%m%d%H%M%S%f') self.doppler_predict = float(doppinfo['Predict_doppler']) self.doppler_DAR = float(doppinfo['DAR_doppler']) coeff = doppinfo['doppler_centroid_coefficients'] rngOrder = int(coeff['number_of_coefficients_first_dimension']) - 1 azOrder = int(coeff['number_of_coefficients_second_dimension']) - 1 self.doppler_coeff = Poly2D.Poly2D() self.doppler_coeff.initPoly(rangeOrder=rngOrder, azimuthOrder=azOrder) self.doppler_coeff.setMeanRange(self.doppler_ref_range) self.doppler_coeff.setMeanAzimuth( secondsSinceMidnight(self.doppler_ref_azi)) parms = [] for ii in range(azOrder + 1): row = [] for jj in range(rngOrder + 1): key = 'a%d%d' % (ii, jj) val = float(coeff[key]) row.append(val) parms.append(row) self.doppler_coeff.setCoeffs(parms) def extractDoppler(self): ''' Evaluate the doppler polynomial and return the average value for now. ''' rmin = self.frame.getStartingRange() rmax = self.frame.getFarRange() rmid = 0.5 * (rmin + rmax) delr = Const.c / (2 * self.frame.instrument.rangeSamplingRate) azmid = secondsSinceMidnight(self.frame.getSensingMid()) print(rmid, self.doppler_coeff.getMeanRange()) print(azmid, self.doppler_coeff.getMeanAzimuth()) if self.doppler_coeff is None: raise Exception( 'ASF PARFILE was not provided. Cannot determine default doppler.' ) dopav = self.doppler_coeff(azmid, rmid) prf = self.frame.getInstrument().getPulseRepetitionFrequency() quadratic = {} quadratic['a'] = dopav / prf quadratic['b'] = 0. quadratic['c'] = 0. ######Set up the doppler centroid computation just like CSK at mid azimuth order = self.doppler_coeff._rangeOrder rng = np.linspace(rmin, rmax, num=(order + 2)) pix = (rng - rmin) / delr val = [self.doppler_coeff(azmid, x) for x in rng] print(rng, val) print(delr, pix) fit = np.polyfit(pix, val, order) self.frame._dopplerVsPixel = list(fit[::-1]) # self.frame._dopplerVsPixel = [dopav,0.,0.,0.] return quadratic def _decodeSceneReferenceNumber(self, referenceNumber): return referenceNumber
class Risat1_SLC(Sensor): """ Code to read CEOSFormat leader files for Risat-1 SAR data. """ family = "risat1" logging_name = 'isce.sensor.Risat1' parameter_list = (IMAGEFILE, LEADERFILE, METAFILE, DATATYPE) + Sensor.parameter_list @logged def __init__(self, name=''): super().__init__(family=self.__class__.family, name=name) self.imageFile = None self.leaderFile = None #####Specific doppler functions for RISAT1 self.doppler_coeff = None self.azfmrate_coeff = None self.lineDirection = None self.pixelDirection = None self.frame = Frame() self.frame.configure() self.constants = { 'antennaLength': 6, } self.TxPolMap = { 1: 'V', 2: 'H', 3: 'L', 4: 'R', } self.RxPolMap = { 1: 'V', 2: 'H', } def getFrame(self): return self.frame def parse(self): self.leaderFile = LeaderFile(self, file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(self, file=self._imageFile) self.imageFile.parse() self.populateMetadata() def populateMetadata(self): """ Create the appropriate metadata objects from our CEOSFormat metadata """ frame = self._decodeSceneReferenceNumber( self.leaderFile.sceneHeaderRecord. metadata['Scene reference number']) try: rangePixelSize = Const.c / (2 * self.leaderFile.sceneHeaderRecord. metadata['Range sampling rate']) except ZeroDivisionError: rangePixelSize = 0 print( 'Average terrain height: ', 1000 * self.leaderFile. sceneHeaderRecord.metadata['Average terrain height in km']) ins = self.frame.getInstrument() platform = ins.getPlatform() platform.setMission(self.leaderFile.sceneHeaderRecord. metadata['Sensor platform mission identifier']) platform.setAntennaLength(self.constants['antennaLength']) platform.setPlanet(Planet(pname='Earth')) ins.setRadarWavelength( self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength']) ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord. metadata['Incidence angle at scene centre']) self.frame.getInstrument().setPulseRepetitionFrequency( self.leaderFile.sceneHeaderRecord. metadata['Pulse Repetition Frequency']) ins.setRangePixelSize(rangePixelSize) ins.setRangeSamplingRate( self.leaderFile.sceneHeaderRecord.metadata['Range sampling rate']) ins.setPulseLength( self.leaderFile.sceneHeaderRecord.metadata['Range pulse length']) chirpPulseBandwidth = self.leaderFile.processingRecord.metadata[ 'Pulse bandwidth code'] * 1e4 ins.setChirpSlope( chirpPulseBandwidth / self.leaderFile.sceneHeaderRecord.metadata['Range pulse length']) ins.setInPhaseValue(0.0) ins.setQuadratureValue(0.0) self.lineDirection = self.leaderFile.sceneHeaderRecord.metadata[ 'Time direction indicator along line direction'].strip() self.pixelDirection = self.leaderFile.sceneHeaderRecord.metadata[ 'Time direction indicator along pixel direction'].strip() ######RISAT-1 sensor orientation convention is opposite to ours lookSide = self.leaderFile.processingRecord.metadata[ 'Sensor orientation'] if lookSide == 'RIGHT': platform.setPointingDirection(1) elif lookSide == 'LEFT': platform.setPointingDirection(-1) else: raise Exception('Unknown look side') print('Leader file look side: ', lookSide) self.frame.setFrameNumber(frame) self.frame.setOrbitNumber( self.leaderFile.sceneHeaderRecord.metadata['Orbit number']) self.frame.setProcessingFacility( self.leaderFile.sceneHeaderRecord. metadata['Processing facility identifier']) self.frame.setProcessingSystem( self.leaderFile.sceneHeaderRecord. metadata['Processing system identifier']) self.frame.setProcessingSoftwareVersion( self.leaderFile.sceneHeaderRecord. metadata['Processing version identifier']) self.frame.setNumberOfLines( self.imageFile.imageFDR.metadata['Number of lines per data set']) self.frame.setNumberOfSamples( self.imageFile.imageFDR. metadata['Number of pixels per line per SAR channel']) ###### self.frame.getOrbit().setOrbitSource('Header') self.frame.getOrbit().setOrbitQuality( self.leaderFile.platformPositionRecord. metadata['Orbital elements designator']) t0 = datetime.datetime(year=2000 + self.leaderFile.platformPositionRecord. metadata['Year of data point'], month=self.leaderFile.platformPositionRecord. metadata['Month of data point'], day=self.leaderFile.platformPositionRecord. metadata['Day of data point']) t0 = t0 + datetime.timedelta( seconds=self.leaderFile.platformPositionRecord. metadata['Seconds of day']) #####Read in orbit in inertial coordinates orb = Orbit() deltaT = self.leaderFile.platformPositionRecord.metadata[ 'Time interval between DATA points'] numPts = self.leaderFile.platformPositionRecord.metadata[ 'Number of data points'] for i in range(numPts): vec = StateVector() t = t0 + datetime.timedelta(seconds=i * deltaT) vec.setTime(t) dataPoints = self.leaderFile.platformPositionRecord.metadata[ 'Positional Data Points'][i] pos = [ dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z'] ] vel = [ dataPoints['Velocity vector X'], dataPoints['Velocity vector Y'], dataPoints['Velocity vector Z'] ] vec.setPosition(pos) vec.setVelocity(vel) orb.addStateVector(vec) #####Convert orbits from ECI to ECR frame t0 = orb._stateVectors[0]._time ang = self.leaderFile.platformPositionRecord.metadata[ 'Greenwich mean hour angle'] cOrb = ECI2ECR(orb, GAST=ang, epoch=t0) iOrb = cOrb.convert() #####Extend the orbits by a few points #####Expect large azimuth shifts - absolutely needed #####Since CEOS contains state vectors that barely covers scene extent planet = self.frame.instrument.platform.planet orbExt = OrbitExtender() orbExt.configure() orbExt._newPoints = 4 newOrb = orbExt.extendOrbit(iOrb) orb = self.frame.getOrbit() for sv in newOrb: orb.addStateVector(sv) self.doppler_coeff = [ self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency centroid constant term'], self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency centroid linear term'], self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency centroid quadratic term'] ] self.azfmrate_coeff = [ self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency rate constant term'], self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency rate linear term'], self.leaderFile.sceneHeaderRecord. metadata['Cross track Doppler frequency rate quadratic term'] ] def extractImage(self): import isceobj if (self.imageFile is None) or (self.leaderFile is None): self.parse() try: out = open(self.output, 'wb') except IOError as strerr: self.logger.error("IOError: %s" % strerr) self.imageFile.extractImage(output=out, dtype=self._dataType) out.close() self.frame.setSensingStart(self.imageFile.sensingStart) self.frame.setSensingStop(self.imageFile.sensingStop) sensingMid = self.imageFile.sensingStart + datetime.timedelta( seconds=0.5 * (self.imageFile.sensingStop - self.imageFile.sensingStart).total_seconds()) self.frame.setSensingMid(sensingMid) self.frame.setStartingRange(self.imageFile.nearRange) self.frame.setFarRange(self.imageFile.farRange) # self.doppler_coeff = self.imageFile.dopplerCoeff self.frame.getInstrument().setPulseRepetitionFrequency( self.imageFile.prf) pol = self.TxPolMap[int( self.imageFile.polarization[0])] + self.TxPolMap[int( self.imageFile.polarization[1])] self.frame.setPolarization(pol) rawImage = isceobj.createSlcImage() rawImage.setByteOrder('l') rawImage.setAccessMode('read') rawImage.setFilename(self.output) rawImage.setWidth(self.imageFile.width) rawImage.setXmin(0) rawImage.setXmax(self.imageFile.width) rawImage.renderHdr() self.frame.setImage(rawImage) return def extractDoppler(self): ''' Evaluate the doppler polynomial and return the average value for now. ''' ####For insarApp quadratic = {} quadratic['a'] = self.doppler_coeff[0] / self.frame.getInstrument( ).getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. ###For roiApp ###More accurate self.frame._dopplerVsPixel = self.doppler_coeff return quadratic def _decodeSceneReferenceNumber(self, referenceNumber): return referenceNumber
class ERS_EnviSAT_SLC(Sensor): parameter_list = (ORBIT_TYPE, ORBIT_DIRECTORY, ORBITFILE, IMAGEFILE) + Sensor.parameter_list """ A Class for parsing ERS instrument and imagery files (Envisat format) """ family = 'ers' logging_name = 'isce.sensor.ers_envisat_slc' def __init__(self,family='',name=''): super(ERS_EnviSAT_SLC, self).__init__(family if family else self.__class__.family, name=name) self._imageFile = None #self._instrumentFileData = None #none for ERS self._imageryFileData = None self.dopplerRangeTime = None self.rangeRefTime = None self.logger = logging.getLogger("isce.sensor.ERS_EnviSAT_SLC") self.frame = None self.frameList = [] #NOTE: copied from ERS_SLC.py... only antennaLength used? -SH # Constants are from # J. J. Mohr and S. N. Madsen. Geometric calibration of ERS satellite # SAR images. IEEE T. Geosci. Remote, 39(4):842-850, Apr. 2001. self.constants = {'polarization': 'VV', 'antennaLength': 10, 'lookDirection': 'RIGHT', 'chirpPulseBandwidth': 15.50829e6, 'rangeSamplingRate': 18.962468e6, 'delayTime':6.622e-6, 'iBias': 15.5, 'qBias': 15.5} def getFrame(self): return self.frame def parse(self): """ Parse both imagery and create objects representing the platform, instrument and scene """ self.frame = Frame() self.frame.configure() self._imageFile = ImageryFile(fileName=self._imageFileName) self._imageryFileData = self._imageFile.parse() self.populateMetadata() def populateMetadata(self): self._populatePlatform() self._populateInstrument() self._populateFrame() #self._populateOrbit() if (self._orbitType == 'ODR'): self._populateDelftOrbits() elif (self._orbitType == 'PRC'): self._populatePRCOrbits() elif (self._orbitType == 'PDS'): self._populatePDSOrbits() #else: # self._populateHeaderOrbit() #NOTE: No leader file #NOTE: remove? self.dopplerRangeTime = self._imageryFileData['doppler'] self.rangeRefTime = self._imageryFileData['dopplerOrigin'][0] * 1.0e-9 # print('Doppler confidence: ', 100.0 * self._imageryFileData['dopplerConfidence'][0]) def _populatePlatform(self): """Populate the platform object with metadata""" platform = self.frame.getInstrument().getPlatform() # Populate the Platform and Scene objects platform.setMission("ERS") platform.setPointingDirection(-1) platform.setAntennaLength(self.constants['antennaLength']) platform.setPlanet(Planet(pname="Earth")) def _populateInstrument(self): """Populate the instrument object with metadata""" instrument = self.frame.getInstrument() rangeSampleSpacing = Const.c/(2*self._imageryFileData['rangeSamplingRate']) pri = self._imageryFileData['pri'] ####These shouldnt matter for SLC data since data is already focused. txPulseLength = 512 / 19207680.000000 chirpPulseBandwidth = 16.0e6 chirpSlope = chirpPulseBandwidth/txPulseLength instrument.setRangePixelSize(rangeSampleSpacing) instrument.setPulseLength(txPulseLength) #instrument.setSwath(imageryFileData['SWATH']) instrument.setRadarFrequency(self._imageryFileData['radarFrequency']) instrument.setChirpSlope(chirpSlope) instrument.setRangeSamplingRate(self._imageryFileData['rangeSamplingRate']) instrument.setPulseRepetitionFrequency(1.0/pri) #instrument.setRangeBias(rangeBias) instrument.setInPhaseValue(self.constants['iBias']) instrument.setQuadratureValue(self.constants['qBias']) def _populateFrame(self): """Populate the scene object with metadata""" numberOfLines = self._imageryFileData['numLines'] numberOfSamples = self._imageryFileData['numSamples'] pri = self._imageryFileData['pri'] startingRange = Const.c * float(self._imageryFileData['timeToFirstSample']) * 1.0e-9 / 2.0 rangeSampleSpacing = Const.c/(2*self._imageryFileData['rangeSamplingRate']) farRange = startingRange + numberOfSamples*rangeSampleSpacing first_line_utc = datetime.datetime.strptime(self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f') center_line_utc = datetime.datetime.strptime(self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f') last_line_utc = datetime.datetime.strptime(self._imageryFileData['LAST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f') centerTime = DTUtil.timeDeltaToSeconds(last_line_utc-first_line_utc)/2.0 center_line_utc = center_line_utc + datetime.timedelta(microseconds=int(centerTime*1e6)) self.frame.setStartingRange(startingRange) self.frame.setFarRange(farRange) self.frame.setProcessingFacility(self._imageryFileData['PROC_CENTER']) self.frame.setProcessingSystem(self._imageryFileData['SOFTWARE_VER']) self.frame.setTrackNumber(int(self._imageryFileData['REL_ORBIT'])) self.frame.setOrbitNumber(int(self._imageryFileData['ABS_ORBIT'])) self.frame.setPolarization(self._imageryFileData['MDS1_TX_RX_POLAR']) self.frame.setNumberOfSamples(numberOfSamples) self.frame.setNumberOfLines(numberOfLines) self.frame.setSensingStart(first_line_utc) self.frame.setSensingMid(center_line_utc) self.frame.setSensingStop(last_line_utc) def _populateDelftOrbits(self): """Populate an orbit object with the Delft orbits""" from isceobj.Orbit.ODR import ODR, Arclist self.logger.info("Using Delft Orbits") arclist = Arclist(os.path.join(self._orbitDir,'arclist')) arclist.parse() print(self.frame.getSensingStart()) print(arclist) orbitFile = arclist.getOrbitFile(self.frame.getSensingStart()) #print(orbitFile) odr = ODR(file=os.path.join(self._orbitDir,orbitFile)) startTimePreInterp = self.frame.getSensingStart() - datetime.timedelta(minutes=60) stopTimePreInterp = self.frame.getSensingStop() + datetime.timedelta(minutes=60) odr.parseHeader(startTimePreInterp,stopTimePreInterp) startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) orbit = odr.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def _populatePRCOrbits(self): """Populate an orbit object the D-PAF PRC orbits""" from isceobj.Orbit.PRC import PRC, Arclist self.logger.info("Using PRC Orbits") arclist = Arclist(os.path.join(self._orbitDir,'arclist')) arclist.parse() orbitFile = arclist.getOrbitFile(self.frame.getSensingStart()) self.logger.debug("Using file %s" % (orbitFile)) prc = PRC(file=os.path.join(self._orbitDir,orbitFile)) prc.parse() startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) fullOrbit = prc.getOrbit() orbit = fullOrbit.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def _populatePDSOrbits(self): """ Populate an orbit object using the ERS-2 PDS format """ from isceobj.Orbit.PDS import PDS self.logger.info("Using PDS Orbits") pds = PDS(file=self._orbitFile) pds.parse() startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) fullOrbit = pds.getOrbit() orbit = fullOrbit.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def _populateImage(self,outname,width,length): #farRange = self.frame.getStartingRange() + width*self.frame.getInstrument().getRangeSamplingRate() # Update the NumberOfSamples and NumberOfLines in the Frame object self.frame.setNumberOfSamples(width) self.frame.setNumberOfLines(length) #self.frame.setFarRange(farRange) # Create a RawImage object rawImage = createSlcImage() rawImage.setFilename(outname) rawImage.setAccessMode('read') rawImage.setByteOrder('l') rawImage.setXmin(0) rawImage.setXmax(width) rawImage.setWidth(width) self.frame.setImage(rawImage) def extractImage(self): from datetime import datetime as dt import tempfile as tf self.parse() width = self._imageryFileData['numSamples'] length = self._imageryFileData['numLines'] self._imageFile.extractImage(self.output, width, length) self._populateImage(self.output, width, length) pass def extractDoppler(self): """ Return the doppler centroid as defined in the ASAR file. """ quadratic = {} r0 = self.frame.getStartingRange() dr = self.frame.instrument.getRangePixelSize() width = self.frame.getNumberOfSamples() midr = r0 + (width/2.0) * dr midtime = 2 * midr/ Const.c - self.rangeRefTime fd_mid = 0.0 tpow = midtime for kk in self.dopplerRangeTime: fd_mid += kk * tpow tpow *= midtime ####For insarApp quadratic['a'] = fd_mid/self.frame.getInstrument().getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. ####For roiApp ####More accurate from isceobj.Util import Poly1D coeffs = self.dopplerRangeTime dr = self.frame.getInstrument().getRangePixelSize() rref = 0.5 * Const.c * self.rangeRefTime r0 = self.frame.getStartingRange() norm = 0.5*Const.c/dr dcoeffs = [] for ind, val in enumerate(coeffs): dcoeffs.append( val / (norm**ind)) poly = Poly1D.Poly1D() poly.initPoly(order=len(coeffs)-1) poly.setMean( (rref - r0)/dr - 1.0) poly.setCoeffs(dcoeffs) pix = np.linspace(0, self.frame.getNumberOfSamples(), num=len(coeffs)+1) evals = poly(pix) fit = np.polyfit(pix,evals, len(coeffs)-1) self.frame._dopplerVsPixel = list(fit[::-1]) print('Doppler Fit: ', fit[::-1]) return quadratic
class Track(object): """A class to represent a collection of temporally continuous radar frame objects""" logging_name = "isce.Scene.Track" @logged def __init__(self): # These are attributes representing the starting time and stopping # time of the track # As well as the early and late times (range times) of the track self._startTime = datetime.datetime(year=datetime.MAXYEAR, month=1, day=1) self._stopTime = datetime.datetime(year=datetime.MINYEAR, month=1, day=1) # Hopefully this number is large # enough, Python doesn't appear to have a MAX_FLT variable self._nearRange = float_info.max self._farRange = 0.0 self._frames = [] self._frame = Frame() self._lastFile = '' return None def combineFrames(self, output, frames): attitudeOk = True for frame in frames: self.addFrame(frame) if hasattr(frame, '_attitude'): att = frame.getAttitude() if not att: attitudeOk = False self.createInstrument() self.createTrack(output) self.createOrbit() if attitudeOk: self.createAttitude() return self._frame def createAuxFile(self, fileList, output): import struct from operator import itemgetter import os import array import copy dateIndx = [] cnt = 0 #first sort the files from earlier to latest. use the first element for name in fileList: with open(name, 'rb') as fp: date = fp.read(16) day, musec = struct.unpack('<dd', date) dateIndx.append([day, musec, name]) cnt += 1 sortedDate = sorted(dateIndx, key=itemgetter(0, 1)) #we need to make sure that there are not duplicate points in the orbit since some frames overlap allL = array.array('d') allL1 = array.array('d') name = sortedDate[0][2] size = os.path.getsize(name) // 8 with open(name, 'rb') as fp1: allL.fromfile(fp1, size) lastDay = allL[-2] lastMusec = allL[-1] for j in range(1, len(sortedDate)): name = sortedDate[j][2] size = os.path.getsize(name) // 8 with open(name, 'rb') as fp1: allL1.fromfile(fp1, size) indxFound = None avgPRI = 0 cnt = 0 for i in range(len(allL1) // 2): if i > 0: avgPRI += allL1[2 * i + 1] - allL1[2 * i - 1] cnt += 1 if allL1[2 * i] >= lastDay and allL1[2 * i + 1] > lastMusec: avgPRI //= (cnt - 1) if ( allL1[2 * i + 1] - lastMusec ) > avgPRI / 2: # make sure that the distance in pulse is atleast 1/2 PRI indxFound = 2 * i else: #if not take the next indxFound = 2 * (i + 1) pass break if not indxFound is None: allL.extend(allL1[indxFound:]) lastDay = allL[-2] lastMusec = allL[-1] pass pass with open(output, 'wb') as fp: allL.tofile(fp) return # Add an additional Frame object to the track @type_check(Frame) def addFrame(self, frame): self.logger.info("Adding Frame to Track") self._updateTrackTimes(frame) self._frames.append(frame) return None def createOrbit(self): orbitAll = Orbit() for i in range(len(self._frames)): orbit = self._frames[i].getOrbit() #remember that everything is by reference, so the changes applied to orbitAll will be made to the Orbit #object in self.frame for sv in orbit._stateVectors: orbitAll.addStateVector(sv) # sort the orbit state vecotrs according to time orbitAll._stateVectors.sort(key=lambda sv: sv.time) self.removeDuplicateVectors(orbitAll._stateVectors) self._frame.setOrbit(orbitAll) def removeDuplicateVectors(self, stateVectors): i1 = 0 #remove duplicate state vectors while True: if i1 >= len(stateVectors) - 1: break if stateVectors[i1].time == stateVectors[i1 + 1].time: stateVectors.pop(i1 + 1) #since is sorted by time if is not equal we can pass to the next else: i1 += 1 def createAttitude(self): attitudeAll = Attitude() for i in range(len(self._frames)): attitude = self._frames[i].getAttitude() #remember that everything is by reference, so the changes applied to attitudeAll will be made to the Attitude object in self.frame for sv in attitude._stateVectors: attitudeAll.addStateVector(sv) # sort the attitude state vecotrs according to time attitudeAll._stateVectors.sort(key=lambda sv: sv.time) self.removeDuplicateVectors(attitudeAll._stateVectors) self._frame.setAttitude(attitudeAll) def createInstrument(self): # the platform is already part of the instrument ins = self._frames[0].getInstrument() self._frame.setInstrument(ins) # sometime the startLine computed below from the sensingStart is not #precise and the image are missaligned. #for each pair do an exact mach by comparing the lines around lineStart #file1,2 input files, startLine1 is the estimated start line in the first file #line1 = last line used in the first file #width = width of the files #frameNum1,2 number of the frames in the sequence of frames to stitch #returns a more accurate line1 def findOverlapLine(self, file1, file2, line1, width, frameNum1, frameNum2): import numpy as np import array fin2 = open(file2, 'rb') arr2 = array.array('b') #read full line at the beginning of second file arr2.fromfile(fin2, width) buf2 = np.array(arr2, dtype=np.int8) numTries = 30 # start around line1 and try numTries around line1 # see searchlist to see which lines it searches searchNumLines = 2 #make a sliding window that search for the searchSize samples inside buf2 searchSize = 500 max = 0 indx = None fin1 = open(file1, 'rb') for i in range(numTries): # example line1 = 0,searchNumLine = 2 and i = 0 search = [-2,-1,0,1], i = 1, serach = [-4,-3,2,3] search = list( range(line1 - (i + 1) * searchNumLines, line1 - i * searchNumLines)) search.extend( list( range(line1 + i * searchNumLines, line1 + (i + 1) * searchNumLines))) for k in search: arr1 = array.array('b') #seek to the line k and read +- searchSize/2 samples from the middle of the line fin1.seek(k * width + (width - searchSize) // 2, 0) arr1.fromfile(fin1, searchSize) buf1 = np.array(arr1, dtype=np.int8) found = False for i in np.arange(width - searchSize): lenSame = len( np.nonzero(buf1 == buf2[i:i + searchSize])[0]) if lenSame > max: max = lenSame indx = k if (lenSame == searchSize): found = True break if (found): break if (found): break if not found: self.logger.warning( "Cannot find perfect overlap between frame %d and frame %d. Using acquisition time to find overlap position." % (frameNum1, frameNum2)) fin1.close() fin2.close() print('Match found: ', indx) return indx def reAdjustStartLine(self, sortedList, width): """ Computed the adjusted starting lines based on matching in overlapping regions """ from operator import itemgetter import os #first one always starts from zero startLine = [sortedList[0][0]] outputs = [sortedList[0][1]] for i in range(1, len(sortedList)): # endLine of the first file. we use all the lines of the first file up to endLine endLine = sortedList[i][0] - sortedList[i - 1][0] indx = self.findOverlapLine(sortedList[i - 1][1], sortedList[i][1], endLine, width, i - 1, i) #if indx is not None than indx is the new start line #otherwise we use startLine computed from acquisition time if (indx is not None) and (indx + sortedList[i - 1][0] != sortedList[i][0]): startLine.append(indx + sortedList[i - 1][0]) outputs.append(sortedList[i][1]) self.logger.info( "Changing starting line for frame %d from %d to %d" % (i, endLine, indx)) else: startLine.append(sortedList[i][0]) outputs.append(sortedList[i][1]) return startLine, outputs # Create the actual Track data by concatenating data from # all of the Frames objects together def createTrack(self, output): import os from operator import itemgetter from isceobj import Constants as CN from ctypes import cdll, c_char_p, c_int, c_ubyte, byref lib = cdll.LoadLibrary(os.path.dirname(__file__) + '/concatenate.so') # Perhaps we should check to see if Xmin is 0, if it is not, strip off the header self.logger.info( "Adjusting Sampling Window Start Times for all Frames") # Iterate over each frame object, and calculate the number of samples with which to pad it on the left and right outputs = [] totalWidth = 0 auxList = [] for frame in self._frames: # Calculate the amount of padding thisNearRange = frame.getStartingRange() thisFarRange = frame.getFarRange() left_pad = int( round((thisNearRange - self._nearRange) * frame.getInstrument().getRangeSamplingRate() / (CN.SPEED_OF_LIGHT / 2.0))) * 2 right_pad = int( round((self._farRange - thisFarRange) * frame.getInstrument().getRangeSamplingRate() / (CN.SPEED_OF_LIGHT / 2.0))) * 2 width = frame.getImage().getXmax() if width - int(width) != 0: raise ValueError("frame Xmax is not an integer") else: width = int(width) input = frame.getImage().getFilename() # tempOutput = os.path.basename(os.tmpnam()) # Some temporary filename with tempfile.NamedTemporaryFile(dir='.') as f: tempOutput = f.name pad_value = int(frame.getInstrument().getInPhaseValue()) if totalWidth < left_pad + width + right_pad: totalWidth = left_pad + width + right_pad # Resample this frame with swst_resample input_c = c_char_p(bytes(input, 'utf-8')) output_c = c_char_p(bytes(tempOutput, 'utf-8')) width_c = c_int(width) left_pad_c = c_int(left_pad) right_pad_c = c_int(right_pad) pad_value_c = c_ubyte(pad_value) lib.swst_resample(input_c, output_c, byref(width_c), byref(left_pad_c), byref(right_pad_c), byref(pad_value_c)) outputs.append(tempOutput) auxList.append(frame.auxFile) #this step construct the aux file withe the pulsetime info for the all set of frames self.createAuxFile(auxList, output + '.aux') # This assumes that all of the frames to be concatenated are sampled at the same PRI prf = self._frames[0].getInstrument().getPulseRepetitionFrequency() # Calculate the starting output line of each scene i = 0 lineSort = [] # the listSort has 2 elements: a line start number which is the position of that specific frame # computed from acquisition time and the corresponding file name for frame in self._frames: startLine = int( round( DTU.timeDeltaToSeconds(frame.getSensingStart() - self._startTime) * prf)) lineSort.append([startLine, outputs[i]]) i += 1 sortedList = sorted( lineSort, key=itemgetter(0)) # sort by line number i.e. acquisition time startLines, outputs = self.reAdjustStartLine(sortedList, totalWidth) self.logger.info("Concatenating Frames along Track") # this is a hack since the length of the file could be actually different from the one computed using start and stop time. it only matters the last frame added import os fileSize = os.path.getsize(outputs[-1]) numLines = fileSize // totalWidth + startLines[-1] totalLines_c = c_int(numLines) # Next, call frame_concatenate width_c = c_int( totalWidth ) # Width of each frame (with the padding added in swst_resample) numberOfFrames_c = c_int(len(self._frames)) inputs_c = (c_char_p * len(outputs))( ) # These are the inputs to frame_concatenate, but the outputs from swst_resample for kk in range(len(outputs)): inputs_c[kk] = bytes(outputs[kk], 'utf-8') output_c = c_char_p(bytes(output, 'utf-8')) startLines_c = (c_int * len(startLines))() startLines_c[:] = startLines lib.frame_concatenate(output_c, byref(width_c), byref(totalLines_c), byref(numberOfFrames_c), inputs_c, startLines_c) # Clean up the temporary output files from swst_resample for file in outputs: os.unlink(file) orbitNum = self._frames[0].getOrbitNumber() first_line_utc = self._startTime last_line_utc = self._stopTime centerTime = DTU.timeDeltaToSeconds(last_line_utc - first_line_utc) / 2.0 center_line_utc = first_line_utc + datetime.timedelta( microseconds=int(centerTime * 1e6)) procFac = self._frames[0].getProcessingFacility() procSys = self._frames[0].getProcessingSystem() procSoft = self._frames[0].getProcessingSoftwareVersion() pol = self._frames[0].getPolarization() xmin = self._frames[0].getImage().getXmin() self._frame.setOrbitNumber(orbitNum) self._frame.setSensingStart(first_line_utc) self._frame.setSensingMid(center_line_utc) self._frame.setSensingStop(last_line_utc) self._frame.setStartingRange(self._nearRange) self._frame.setFarRange(self._farRange) self._frame.setProcessingFacility(procFac) self._frame.setProcessingSystem(procSys) self._frame.setProcessingSoftwareVersion(procSoft) self._frame.setPolarization(pol) self._frame.setNumberOfLines(numLines) self._frame.setNumberOfSamples(width) # add image to frame rawImage = isceobj.createRawImage() rawImage.setByteOrder('l') rawImage.setFilename(output) rawImage.setAccessMode('r') rawImage.setWidth(totalWidth) rawImage.setXmax(totalWidth) rawImage.setXmin(xmin) self._frame.setImage(rawImage) # Extract the early, late, start and stop times from a Frame object # And use this information to update def _updateTrackTimes(self, frame): if (frame.getSensingStart() < self._startTime): self._startTime = frame.getSensingStart() if (frame.getSensingStop() > self._stopTime): self._stopTime = frame.getSensingStop() if (frame.getStartingRange() < self._nearRange): self._nearRange = frame.getStartingRange() if (frame.getFarRange() > self._farRange): self._farRange = frame.getFarRange() pass pass pass
class ICEYE_SLC(Sensor): """ A class representing a Level1Product meta data. Level1Product(hdf5=h5filename) will parse the hdf5 file and produce an object with attributes for metadata. """ parameter_list = (HDF5, APPLY_SLANT_RANGE_PHASE) + Sensor.parameter_list logging_name = 'isce.Sensor.ICEYE_SLC' family = 'iceye_slc' def __init__(self, family='', name=''): super(ICEYE_SLC, self).__init__(family if family else self.__class__.family, name=name) self.frame = Frame() self.frame.configure() # Some extra processing parameters unique to CSK SLC (currently) self.dopplerRangeTime = [] self.dopplerAzimuthTime = [] self.azimuthRefTime = None self.rangeRefTime = None self.rangeFirstTime = None self.rangeLastTime = None self.lookMap = {'RIGHT': -1, 'LEFT': 1} return def __getstate__(self): d = dict(self.__dict__) del d['logger'] return d def __setstate__(self, d): self.__dict__.update(d) self.logger = logging.getLogger('isce.Sensor.ICEYE_SLC') return def getFrame(self): return self.frame def parse(self): try: fp = h5py.File(self.hdf5, 'r') except Exception as strerr: self.logger.error("IOError: %s" % strerr) return None self.populateMetadata(fp) fp.close() def populateMetadata(self, file): """ Populate our Metadata objects """ self._populatePlatform(file) self._populateInstrument(file) self._populateFrame(file) self._populateOrbit(file) self._populateExtras(file) def _populatePlatform(self, file): platform = self.frame.getInstrument().getPlatform() platform.setMission(file['satellite_name'][()]) platform.setPointingDirection( self.lookMap[file['look_side'][()].upper()]) platform.setPlanet(Planet(pname="Earth")) ####This is an approximation for spotlight mode ####In spotlight mode, antenna length changes with azimuth position platform.setAntennaLength(2 * file['azimuth_ground_spacing'][()]) assert (file['range_looks'][()] == 1) assert (file['azimuth_looks'][()] == 1) def _populateInstrument(self, file): instrument = self.frame.getInstrument() rangePixelSize = file['slant_range_spacing'][()] instrument.setRadarWavelength(Const.c / file['carrier_frequency'][()]) instrument.setPulseRepetitionFrequency(file['processing_prf'][()]) instrument.setRangePixelSize(rangePixelSize) instrument.setPulseLength(file['chirp_duration'][()]) instrument.setChirpSlope(file['chirp_bandwidth'][()] / file['chirp_duration'][()]) instrument.setRangeSamplingRate(file['range_sampling_rate'][()]) incangle = file['local_incidence_angle'] instrument.setIncidenceAngle(incangle[incangle.size // 2]) def _populateFrame(self, file): rft = file['first_pixel_time'][()] slantRange = rft * Const.c / 2.0 self.frame.setStartingRange(slantRange) sensingStart = datetime.datetime.strptime( file['zerodoppler_start_utc'][()].decode('utf-8'), '%Y-%m-%dT%H:%M:%S.%f') sensingStop = datetime.datetime.strptime( file['zerodoppler_end_utc'][()].decode('utf-8'), '%Y-%m-%dT%H:%M:%S.%f') sensingMid = sensingStart + 0.5 * (sensingStop - sensingStart) self.frame.setPassDirection(file['orbit_direction'][()]) self.frame.setOrbitNumber(file['orbit_absolute_number'][()]) self.frame.setProcessingFacility('ICEYE') self.frame.setProcessingSoftwareVersion( str(file['processor_version'][()])) self.frame.setPolarization(file['polarization'][()]) self.frame.setNumberOfLines(file['number_of_azimuth_samples'][()]) self.frame.setNumberOfSamples(file['number_of_range_samples'][()]) self.frame.setSensingStart(sensingStart) self.frame.setSensingMid(sensingMid) self.frame.setSensingStop(sensingStop) rangePixelSize = self.frame.getInstrument().getRangePixelSize() farRange = slantRange + (self.frame.getNumberOfSamples() - 1) * rangePixelSize self.frame.setFarRange(farRange) def _populateOrbit(self, file): import numpy as np orbit = self.frame.getOrbit() orbit.setReferenceFrame('ECR') orbit.setOrbitSource('Header') t = file['state_vector_time_utc'][:] position = np.zeros((t.size, 3)) position[:, 0] = file['posX'][:] position[:, 1] = file['posY'][:] position[:, 2] = file['posZ'][:] velocity = np.zeros((t.size, 3)) velocity[:, 0] = file['velX'][:] velocity[:, 1] = file['velY'][:] velocity[:, 2] = file['velZ'][:] for ii in range(t.size): vec = StateVector() vec.setTime( datetime.datetime.strptime(t[ii][0].decode('utf-8'), '%Y-%m-%dT%H:%M:%S.%f')) vec.setPosition( [position[ii, 0], position[ii, 1], position[ii, 2]]) vec.setVelocity( [velocity[ii, 0], velocity[ii, 1], velocity[ii, 2]]) orbit.addStateVector(vec) def _populateExtras(self, file): """ Populate some of the extra fields unique to processing TSX data. In the future, other sensors may need this information as well, and a re-organization may be necessary. """ import numpy as np self.dcpoly = np.mean(file['dc_estimate_coeffs'][:], axis=0) def extractImage(self): import numpy as np import h5py self.parse() fid = h5py.File(self.hdf5, 'r') si = fid['s_i'] sq = fid['s_q'] nLines = si.shape[0] spectralShift = 2 * self.frame.getInstrument().getRangePixelSize( ) / self.frame.getInstrument().getRadarWavelength() spectralShift -= np.floor(spectralShift) phsShift = np.exp(-1j * 2 * np.pi * spectralShift * np.arange(si.shape[1])) with open(self.output, 'wb') as fout: for ii in range(nLines): line = (si[ii, :] + 1j * sq[ii, :]) if self.applySlantRangePhase: line *= phsShift line.astype(np.complex64).tofile(fout) fid.close() slcImage = isceobj.createSlcImage() slcImage.setFilename(self.output) slcImage.setXmin(0) slcImage.setXmax(self.frame.getNumberOfSamples()) slcImage.setWidth(self.frame.getNumberOfSamples()) slcImage.setAccessMode('r') self.frame.setImage(slcImage) def extractDoppler(self): """ Return the doppler centroid as defined in the HDF5 file. """ import numpy as np quadratic = {} rangePixelSize = self.frame.getInstrument().getRangePixelSize() rt0 = self.frame.getStartingRange() / (2 * Const.c) rt1 = rt0 + ((self.frame.getNumberOfSamples() - 1) * rangePixelSize) / (2 * Const.c) ####insarApp style quadratic['a'] = np.polyval(self.dcpoly, 0.5 * (rt0 + rt1)) / self.frame.PRF quadratic['b'] = 0. quadratic['c'] = 0. ####For roiApp more accurate ####Convert stuff to pixel wise coefficients x = np.linspace(rt0, rt1, num=len(self.dcpoly) + 1) pix = np.linspace(0, self.frame.getNumberOfSamples(), num=len(self.dcpoly) + 1) evals = np.polyval(self.dcpoly, x) fit = np.polyfit(pix, evals, len(self.dcpoly) - 1) self.frame._dopplerVsPixel = list(fit[::-1]) print('Doppler Fit: ', self.frame._dopplerVsPixel) return quadratic