class ERS(Sensor): family = 'ers' logging_name = 'isce.sensor.ers' 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._leaderFile = None self._imageFile = None self.frameList = [] 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(pname='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.warning( "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()) self.logger.info('Using ODR file: ' + orbitFile) 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 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 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 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 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 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 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 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(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 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 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 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 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 ', '') format_str = '%Y-%m-%d %H:%M:%S' if '.' in referenceUTC: format_str += '.%f' referenceUTC = datetime.datetime.strptime(referenceUTC, format_str) 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 ', '') format_str = '%Y-%m-%d %H:%M:%S' if '.' in referenceUTC: format_str += '.%f' t0 = datetime.datetime.strptime(referenceUTC, format_str) 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] # force casting to complex64 with ds.astype(np.complex64): with open(self.output, 'wb') as fout: for ii in range(nLines): ds[ii, :].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 Risat1(Sensor): """ Code to read CEOSFormat leader files for Risat-1 SAR data. """ family = "risat1" logging_name = 'isce.sensor.Risat1' parameter_list = (IMAGEFILE, LEADERFILE, METAFILE) + 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.lineDirection = None self.pixelDirection = 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() 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 height: ', 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.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']) 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.setChirpSlope(7.5e12) ins.setInPhaseValue(127.0) ins.setQuadratureValue(127.0) 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') 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=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 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() #####Extend the orbits by a few points planet = self.frame.instrument.platform.planet orbExt = OrbitExtender() orbExt.configure() orbExt._newPoints = 4 newOrb = orbExt.extendOrbit(wgsorb) orb = self.frame.getOrbit() for sv in newOrb: orb.addStateVector(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() 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) dr = self.frame.instrument.rangePixelSize self.frame.setStartingRange(self.imageFile.nearRange) self.frame.setFarRange(self.imageFile.nearRange + (self.imageFile.width - 1) * dr) self.doppler_coeff = self.imageFile.dopplerCoeff self.frame.getInstrument().setPulseRepetitionFrequency( self.imageFile.prf) self.frame.instrument.setPulseLength(self.imageFile.chirpLength) print('Pulse length: ', self.imageFile.chirpLength) print('Roll angle: ', self.imageFile.roll) if self.imageFile.roll > 0.: self.frame.instrument.platform.setPointingDirection(1) else: self.frame.instrument.platform.setPointingDirection(-1) rawImage = isceobj.createRawImage() rawImage.setByteOrder('l') rawImage.setAccessMode('read') rawImage.setFilename(self.output) rawImage.setWidth(self.imageFile.width * 2) rawImage.setXmin(0) rawImage.setXmax(self.imageFile.width * 2) rawImage.renderHdr() self.frame.setImage(rawImage) return def extractDoppler(self): ''' Evaluate the doppler polynomial and return the average value for now. ''' print('Doppler: ', self.doppler_coeff) quadratic = {} quadratic['a'] = self.doppler_coeff[1] / self.frame.getInstrument( ).getPulseRepetitionFrequency() quadratic['b'] = 0. quadratic['c'] = 0. return quadratic def _decodeSceneReferenceNumber(self, referenceNumber): return referenceNumber
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 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