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
