class UAVSAR_HDF5_SLC(Sensor):
"""
A class representing a Level1Product meta data.
Level1Product(hdf5=h5filename) will parse the hdf5
file and produce an object with attributes for metadata.
"""
parameter_list = (HDF5, FREQUENCY, POLARIZATION) + Sensor.parameter_list
logging_name = 'isce.Sensor.UAVSAR_HDF5_SLC'
family = 'uavsar_hdf5_slc'
def __init__(self,
family='',
name=''): # , frequency='frequencyA', polarization='HH'):
super(UAVSAR_HDF5_SLC,
self).__init__(family if family else self.__class__.family,
name=name)
self.frame = Frame()
self.frame.configure()
# Some extra processing parameters unique to UAVSAR HDF5 SLC (currently)
self.dopplerRangeTime = []
self.dopplerAzimuthTime = []
self.azimuthRefTime = None
self.rangeRefTime = None
self.rangeFirstTime = None
self.rangeLastTime = None
#self.frequency = frequency
#self.polarization = polarization
self.lookMap = {'right': -1, 'left': 1}
return
def __getstate__(self):
d = dict(self.__dict__)
del d['logger']
return d
def __setstate__(self, d):
self.__dict__.update(d)
self.logger = logging.getLogger('isce.Sensor.UAVSAR_HDF5_SLC')
return
def getFrame(self):
return self.frame
def parse(self):
try:
fp = h5py.File(self.hdf5, 'r')
except Exception as strerr:
self.logger.error("IOError: %s" % strerr)
return None
self.populateMetadata(fp)
fp.close()
def populateMetadata(self, file):
"""
Populate our Metadata objects
"""
self._populatePlatform(file)
self._populateInstrument(file)
self._populateFrame(file)
self._populateOrbit(file)
def _populatePlatform(self, file):
platform = self.frame.getInstrument().getPlatform()
platform.setMission(
file['/science/LSAR/identification'].get('missionId')[(
)].decode('utf-8'))
platform.setPointingDirection(
self.lookMap[file['/science/LSAR/identification'].get(
'lookDirection')[()].decode('utf-8')])
platform.setPlanet(Planet(pname="Earth"))
# We are not using this value anywhere. Let's fix it for now.
platform.setAntennaLength(12.0)
def _populateInstrument(self, file):
instrument = self.frame.getInstrument()
rangePixelSize = file['/science/LSAR/SLC/swaths/' + self.frequency +
'/slantRangeSpacing'][()]
wvl = SPEED_OF_LIGHT / file['/science/LSAR/SLC/swaths/' +
self.frequency +
'/processedCenterFrequency'][()]
instrument.setRadarWavelength(wvl)
instrument.setPulseRepetitionFrequency(
1.0 / file['/science/LSAR/SLC/swaths/zeroDopplerTimeSpacing'][()])
rangePixelSize = file['/science/LSAR/SLC/swaths/' + self.frequency +
'/slantRangeSpacing'][()]
instrument.setRangePixelSize(rangePixelSize)
# Chrip slope and length only are used in the split spectrum workflow to compute the bandwidth.
# Therefore fixing it to 1.0 won't breack anything
Chirp_slope = 1.0
rangeBandwidth = file['/science/LSAR/SLC/swaths/' + self.frequency +
'/processedRangeBandwidth'][()]
Chirp_length = rangeBandwidth / Chirp_slope
instrument.setPulseLength(Chirp_length)
instrument.setChirpSlope(Chirp_slope)
rangeSamplingFrequency = SPEED_OF_LIGHT / 2. / rangePixelSize
instrument.setRangeSamplingRate(rangeSamplingFrequency)
incangle = 0.0
instrument.setIncidenceAngle(incangle)
def _populateFrame(self, file):
slantRange = file['/science/LSAR/SLC/swaths/' + self.frequency +
'/slantRange'][0]
self.frame.setStartingRange(slantRange)
referenceUTC = file['/science/LSAR/SLC/swaths/zeroDopplerTime'].attrs[
'units'].decode('utf-8')
referenceUTC = referenceUTC.replace('seconds since ', '')
referenceUTC = datetime.datetime.strptime(referenceUTC,
'%Y-%m-%d %H:%M:%S')
relStart = file['/science/LSAR/SLC/swaths/zeroDopplerTime'][0]
relEnd = file['/science/LSAR/SLC/swaths/zeroDopplerTime'][-1]
relMid = 0.5 * (relStart + relEnd)
sensingStart = self._combineDateTime(referenceUTC, relStart)
sensingStop = self._combineDateTime(referenceUTC, relEnd)
sensingMid = self._combineDateTime(referenceUTC, relMid)
self.frame.setPassDirection(
file['/science/LSAR/identification'].get('orbitPassDirection')[(
)].decode('utf-8'))
self.frame.setOrbitNumber(
file['/science/LSAR/identification'].get('trackNumber')[()])
self.frame.setProcessingFacility('JPL')
self.frame.setProcessingSoftwareVersion(
file['/science/LSAR/SLC/metadata/processingInformation/algorithms']
.get('ISCEVersion')[()].decode('utf-8'))
self.frame.setPolarization(self.polarization)
self.frame.setNumberOfLines(
file['/science/LSAR/SLC/swaths/' + self.frequency + '/' +
self.polarization].shape[0])
self.frame.setNumberOfSamples(
file['/science/LSAR/SLC/swaths/' + self.frequency + '/' +
self.polarization].shape[1])
self.frame.setSensingStart(sensingStart)
self.frame.setSensingMid(sensingMid)
self.frame.setSensingStop(sensingStop)
rangePixelSize = self.frame.instrument.rangePixelSize
farRange = slantRange + (self.frame.getNumberOfSamples() -
1) * rangePixelSize
self.frame.setFarRange(farRange)
def _populateOrbit(self, file):
orbit = self.frame.getOrbit()
orbit.setReferenceFrame('ECR')
orbit.setOrbitSource('Header')
referenceUTC = file['/science/LSAR/SLC/swaths/zeroDopplerTime'].attrs[
'units'].decode('utf-8')
referenceUTC = referenceUTC.replace('seconds since ', '')
t0 = datetime.datetime.strptime(referenceUTC, '%Y-%m-%d %H:%M:%S')
t = file['/science/LSAR/SLC/metadata/orbit/time']
position = file['/science/LSAR/SLC/metadata/orbit/position']
velocity = file['/science/LSAR/SLC/metadata/orbit/velocity']
for i in range(len(position)):
vec = StateVector()
dt = t0 + datetime.timedelta(seconds=t[i])
vec.setTime(dt)
vec.setPosition([position[i, 0], position[i, 1], position[i, 2]])
vec.setVelocity([velocity[i, 0], velocity[i, 1], velocity[i, 2]])
orbit.addStateVector(vec)
def extractImage(self):
import numpy as np
import h5py
self.parse()
fid = h5py.File(self.hdf5, 'r')
ds = fid['/science/LSAR/SLC/swaths/' + self.frequency + '/' +
self.polarization]
nLines = ds.shape[0]
with open(self.output, 'wb') as fout:
for ii in range(nLines):
ds[ii, :].astype(np.complex64).tofile(fout)
fid.close()
slcImage = isceobj.createSlcImage()
slcImage.setFilename(self.output)
slcImage.setXmin(0)
slcImage.setXmax(self.frame.getNumberOfSamples())
slcImage.setWidth(self.frame.getNumberOfSamples())
slcImage.setAccessMode('r')
slcImage.renderHdr()
self.frame.setImage(slcImage)
def _parseNanoSecondTimeStamp(self, timestamp):
"""
Parse a date-time string with nanosecond precision and return a datetime object
"""
dateTime, nanoSeconds = timestamp.decode('utf-8').split('.')
microsec = float(nanoSeconds) * 1e-3
dt = datetime.datetime.strptime(dateTime, '%Y-%m-%d %H:%M:%S')
dt = dt + datetime.timedelta(microseconds=microsec)
return dt
def _combineDateTime(self, dobj, secsstr):
'''Takes the date from dobj and time from secs to spit out a date time object.
'''
sec = float(secsstr)
dt = datetime.timedelta(seconds=sec)
return dobj + dt
def extractDoppler(self):
"""
Return the doppler centroid as defined in the HDF5 file.
"""
import h5py
from scipy.interpolate import UnivariateSpline
import numpy as np
h5 = h5py.File(self.hdf5, 'r')
# extract the 2D LUT of Doppler and choose only one range line as the data duplicates for other range lines
dop = h5['/science/LSAR/SLC/metadata/processingInformation/parameters/'
+ self.frequency + '/dopplerCentroid'][0, :]
rng = h5[
'/science/LSAR/SLC/metadata/processingInformation/parameters/slantRange']
# extract the slant range of the image grid
imgRng = h5['/science/LSAR/SLC/swaths/' + self.frequency +
'/slantRange']
# use only part of the slant range that closely covers image ranges and ignore the rest
ind0 = np.argmin(np.abs(rng - imgRng[0])) - 1
ind0 = np.max([0, ind0])
ind1 = np.argmin(np.abs(rng - imgRng[-1])) + 1
ind1 = np.min([ind1, rng.shape[0]])
dop = dop[ind0:ind1]
rng = rng[ind0:ind1]
f = UnivariateSpline(rng, dop)
imgDop = f(imgRng)
dr = imgRng[1] - imgRng[0]
pix = (imgRng - imgRng[0]) / dr
fit = np.polyfit(pix, imgDop, 41)
self.frame._dopplerVsPixel = list(fit[::-1])
####insarApp style (doesn't get used for stripmapApp). A fixed Doppler at the middle of the scene
quadratic = {}
quadratic['a'] = imgDop[int(
imgDop.shape[0] /
2)] / self.frame.getInstrument().getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
return quadratic
class Track(object):
"""A class to represent a collection of temporally continuous radar frame
objects"""
logging_name = "isce.Scene.Track"
@logged
def __init__(self):
# These are attributes representing the starting time and stopping
# time of the track
# As well as the early and late times (range times) of the track
self._startTime = datetime.datetime(year=datetime.MAXYEAR,
month=1,
day=1)
self._stopTime = datetime.datetime(year=datetime.MINYEAR,
month=1,
day=1)
# Hopefully this number is large
# enough, Python doesn't appear to have a MAX_FLT variable
self._nearRange = float_info.max
self._farRange = 0.0
self._frames = []
self._frame = Frame()
self._lastFile = ''
return None
def combineFrames(self, output, frames):
attitudeOk = True
for frame in frames:
self.addFrame(frame)
if hasattr(frame, '_attitude'):
att = frame.getAttitude()
if not att:
attitudeOk = False
self.createInstrument()
self.createTrack(output)
self.createOrbit()
if attitudeOk:
self.createAttitude()
return self._frame
def createAuxFile(self, fileList, output):
import struct
from operator import itemgetter
import os
import array
import copy
dateIndx = []
cnt = 0
#first sort the files from earlier to latest. use the first element
for name in fileList:
with open(name, 'rb') as fp:
date = fp.read(16)
day, musec = struct.unpack('<dd', date)
dateIndx.append([day, musec, name])
cnt += 1
sortedDate = sorted(dateIndx, key=itemgetter(0, 1))
#we need to make sure that there are not duplicate points in the orbit since some frames overlap
allL = array.array('d')
allL1 = array.array('d')
name = sortedDate[0][2]
size = os.path.getsize(name) // 8
with open(name, 'rb') as fp1:
allL.fromfile(fp1, size)
lastDay = allL[-2]
lastMusec = allL[-1]
for j in range(1, len(sortedDate)):
name = sortedDate[j][2]
size = os.path.getsize(name) // 8
with open(name, 'rb') as fp1:
allL1.fromfile(fp1, size)
indxFound = None
avgPRI = 0
cnt = 0
for i in range(len(allL1) // 2):
if i > 0:
avgPRI += allL1[2 * i + 1] - allL1[2 * i - 1]
cnt += 1
if allL1[2 * i] >= lastDay and allL1[2 * i + 1] > lastMusec:
avgPRI //= (cnt - 1)
if (
allL1[2 * i + 1] - lastMusec
) > avgPRI / 2: # make sure that the distance in pulse is atleast 1/2 PRI
indxFound = 2 * i
else: #if not take the next
indxFound = 2 * (i + 1)
pass
break
if not indxFound is None:
allL.extend(allL1[indxFound:])
lastDay = allL[-2]
lastMusec = allL[-1]
pass
pass
with open(output, 'wb') as fp:
allL.tofile(fp)
return
# Add an additional Frame object to the track
@type_check(Frame)
def addFrame(self, frame):
self.logger.info("Adding Frame to Track")
self._updateTrackTimes(frame)
self._frames.append(frame)
return None
def createOrbit(self):
orbitAll = Orbit()
for i in range(len(self._frames)):
orbit = self._frames[i].getOrbit()
#remember that everything is by reference, so the changes applied to orbitAll will be made to the Orbit
#object in self.frame
for sv in orbit._stateVectors:
orbitAll.addStateVector(sv)
# sort the orbit state vecotrs according to time
orbitAll._stateVectors.sort(key=lambda sv: sv.time)
self.removeDuplicateVectors(orbitAll._stateVectors)
self._frame.setOrbit(orbitAll)
def removeDuplicateVectors(self, stateVectors):
i1 = 0
#remove duplicate state vectors
while True:
if i1 >= len(stateVectors) - 1:
break
if stateVectors[i1].time == stateVectors[i1 + 1].time:
stateVectors.pop(i1 + 1)
#since is sorted by time if is not equal we can pass to the next
else:
i1 += 1
def createAttitude(self):
attitudeAll = Attitude()
for i in range(len(self._frames)):
attitude = self._frames[i].getAttitude()
#remember that everything is by reference, so the changes applied to attitudeAll will be made to the Attitude object in self.frame
for sv in attitude._stateVectors:
attitudeAll.addStateVector(sv)
# sort the attitude state vecotrs according to time
attitudeAll._stateVectors.sort(key=lambda sv: sv.time)
self.removeDuplicateVectors(attitudeAll._stateVectors)
self._frame.setAttitude(attitudeAll)
def createInstrument(self):
# the platform is already part of the instrument
ins = self._frames[0].getInstrument()
self._frame.setInstrument(ins)
# sometime the startLine computed below from the sensingStart is not
#precise and the image are missaligned.
#for each pair do an exact mach by comparing the lines around lineStart
#file1,2 input files, startLine1 is the estimated start line in the first file
#line1 = last line used in the first file
#width = width of the files
#frameNum1,2 number of the frames in the sequence of frames to stitch
#returns a more accurate line1
def findOverlapLine(self, file1, file2, line1, width, frameNum1,
frameNum2):
import numpy as np
import array
fin2 = open(file2, 'rb')
arr2 = array.array('b')
#read full line at the beginning of second file
arr2.fromfile(fin2, width)
buf2 = np.array(arr2, dtype=np.int8)
numTries = 30
# start around line1 and try numTries around line1
# see searchlist to see which lines it searches
searchNumLines = 2
#make a sliding window that search for the searchSize samples inside buf2
searchSize = 500
max = 0
indx = None
fin1 = open(file1, 'rb')
for i in range(numTries):
# example line1 = 0,searchNumLine = 2 and i = 0 search = [-2,-1,0,1], i = 1, serach = [-4,-3,2,3]
search = list(
range(line1 - (i + 1) * searchNumLines,
line1 - i * searchNumLines))
search.extend(
list(
range(line1 + i * searchNumLines,
line1 + (i + 1) * searchNumLines)))
for k in search:
arr1 = array.array('b')
#seek to the line k and read +- searchSize/2 samples from the middle of the line
fin1.seek(k * width + (width - searchSize) // 2, 0)
arr1.fromfile(fin1, searchSize)
buf1 = np.array(arr1, dtype=np.int8)
found = False
for i in np.arange(width - searchSize):
lenSame = len(
np.nonzero(buf1 == buf2[i:i + searchSize])[0])
if lenSame > max:
max = lenSame
indx = k
if (lenSame == searchSize):
found = True
break
if (found):
break
if (found):
break
if not found:
self.logger.warning(
"Cannot find perfect overlap between frame %d and frame %d. Using acquisition time to find overlap position."
% (frameNum1, frameNum2))
fin1.close()
fin2.close()
print('Match found: ', indx)
return indx
def reAdjustStartLine(self, sortedList, width):
""" Computed the adjusted starting lines based on matching in overlapping regions """
from operator import itemgetter
import os
#first one always starts from zero
startLine = [sortedList[0][0]]
outputs = [sortedList[0][1]]
for i in range(1, len(sortedList)):
# endLine of the first file. we use all the lines of the first file up to endLine
endLine = sortedList[i][0] - sortedList[i - 1][0]
indx = self.findOverlapLine(sortedList[i - 1][1], sortedList[i][1],
endLine, width, i - 1, i)
#if indx is not None than indx is the new start line
#otherwise we use startLine computed from acquisition time
if (indx is not None) and (indx + sortedList[i - 1][0] !=
sortedList[i][0]):
startLine.append(indx + sortedList[i - 1][0])
outputs.append(sortedList[i][1])
self.logger.info(
"Changing starting line for frame %d from %d to %d" %
(i, endLine, indx))
else:
startLine.append(sortedList[i][0])
outputs.append(sortedList[i][1])
return startLine, outputs
# Create the actual Track data by concatenating data from
# all of the Frames objects together
def createTrack(self, output):
import os
from operator import itemgetter
from isceobj import Constants as CN
from ctypes import cdll, c_char_p, c_int, c_ubyte, byref
lib = cdll.LoadLibrary(os.path.dirname(__file__) + '/concatenate.so')
# Perhaps we should check to see if Xmin is 0, if it is not, strip off the header
self.logger.info(
"Adjusting Sampling Window Start Times for all Frames")
# Iterate over each frame object, and calculate the number of samples with which to pad it on the left and right
outputs = []
totalWidth = 0
auxList = []
for frame in self._frames:
# Calculate the amount of padding
thisNearRange = frame.getStartingRange()
thisFarRange = frame.getFarRange()
left_pad = int(
round((thisNearRange - self._nearRange) *
frame.getInstrument().getRangeSamplingRate() /
(CN.SPEED_OF_LIGHT / 2.0))) * 2
right_pad = int(
round((self._farRange - thisFarRange) *
frame.getInstrument().getRangeSamplingRate() /
(CN.SPEED_OF_LIGHT / 2.0))) * 2
width = frame.getImage().getXmax()
if width - int(width) != 0:
raise ValueError("frame Xmax is not an integer")
else:
width = int(width)
input = frame.getImage().getFilename()
# tempOutput = os.path.basename(os.tmpnam()) # Some temporary filename
with tempfile.NamedTemporaryFile(dir='.') as f:
tempOutput = f.name
pad_value = int(frame.getInstrument().getInPhaseValue())
if totalWidth < left_pad + width + right_pad:
totalWidth = left_pad + width + right_pad
# Resample this frame with swst_resample
input_c = c_char_p(bytes(input, 'utf-8'))
output_c = c_char_p(bytes(tempOutput, 'utf-8'))
width_c = c_int(width)
left_pad_c = c_int(left_pad)
right_pad_c = c_int(right_pad)
pad_value_c = c_ubyte(pad_value)
lib.swst_resample(input_c, output_c, byref(width_c),
byref(left_pad_c), byref(right_pad_c),
byref(pad_value_c))
outputs.append(tempOutput)
auxList.append(frame.auxFile)
#this step construct the aux file withe the pulsetime info for the all set of frames
self.createAuxFile(auxList, output + '.aux')
# This assumes that all of the frames to be concatenated are sampled at the same PRI
prf = self._frames[0].getInstrument().getPulseRepetitionFrequency()
# Calculate the starting output line of each scene
i = 0
lineSort = []
# the listSort has 2 elements: a line start number which is the position of that specific frame
# computed from acquisition time and the corresponding file name
for frame in self._frames:
startLine = int(
round(
DTU.timeDeltaToSeconds(frame.getSensingStart() -
self._startTime) * prf))
lineSort.append([startLine, outputs[i]])
i += 1
sortedList = sorted(
lineSort,
key=itemgetter(0)) # sort by line number i.e. acquisition time
startLines, outputs = self.reAdjustStartLine(sortedList, totalWidth)
self.logger.info("Concatenating Frames along Track")
# this is a hack since the length of the file could be actually different from the one computed using start and stop time. it only matters the last frame added
import os
fileSize = os.path.getsize(outputs[-1])
numLines = fileSize // totalWidth + startLines[-1]
totalLines_c = c_int(numLines)
# Next, call frame_concatenate
width_c = c_int(
totalWidth
) # Width of each frame (with the padding added in swst_resample)
numberOfFrames_c = c_int(len(self._frames))
inputs_c = (c_char_p * len(outputs))(
) # These are the inputs to frame_concatenate, but the outputs from swst_resample
for kk in range(len(outputs)):
inputs_c[kk] = bytes(outputs[kk], 'utf-8')
output_c = c_char_p(bytes(output, 'utf-8'))
startLines_c = (c_int * len(startLines))()
startLines_c[:] = startLines
lib.frame_concatenate(output_c, byref(width_c), byref(totalLines_c),
byref(numberOfFrames_c), inputs_c, startLines_c)
# Clean up the temporary output files from swst_resample
for file in outputs:
os.unlink(file)
orbitNum = self._frames[0].getOrbitNumber()
first_line_utc = self._startTime
last_line_utc = self._stopTime
centerTime = DTU.timeDeltaToSeconds(last_line_utc -
first_line_utc) / 2.0
center_line_utc = first_line_utc + datetime.timedelta(
microseconds=int(centerTime * 1e6))
procFac = self._frames[0].getProcessingFacility()
procSys = self._frames[0].getProcessingSystem()
procSoft = self._frames[0].getProcessingSoftwareVersion()
pol = self._frames[0].getPolarization()
xmin = self._frames[0].getImage().getXmin()
self._frame.setOrbitNumber(orbitNum)
self._frame.setSensingStart(first_line_utc)
self._frame.setSensingMid(center_line_utc)
self._frame.setSensingStop(last_line_utc)
self._frame.setStartingRange(self._nearRange)
self._frame.setFarRange(self._farRange)
self._frame.setProcessingFacility(procFac)
self._frame.setProcessingSystem(procSys)
self._frame.setProcessingSoftwareVersion(procSoft)
self._frame.setPolarization(pol)
self._frame.setNumberOfLines(numLines)
self._frame.setNumberOfSamples(width)
# add image to frame
rawImage = isceobj.createRawImage()
rawImage.setByteOrder('l')
rawImage.setFilename(output)
rawImage.setAccessMode('r')
rawImage.setWidth(totalWidth)
rawImage.setXmax(totalWidth)
rawImage.setXmin(xmin)
self._frame.setImage(rawImage)
# Extract the early, late, start and stop times from a Frame object
# And use this information to update
def _updateTrackTimes(self, frame):
if (frame.getSensingStart() < self._startTime):
self._startTime = frame.getSensingStart()
if (frame.getSensingStop() > self._stopTime):
self._stopTime = frame.getSensingStop()
if (frame.getStartingRange() < self._nearRange):
self._nearRange = frame.getStartingRange()
if (frame.getFarRange() > self._farRange):
self._farRange = frame.getFarRange()
pass
pass
pass
class ERS(Component):
#Parsers.CEOS.CEOSFormat.ceosTypes['text'] =
# {'typeCode': 63, 'subtypeCode': [18,18,18]}
#Parsers.CEOS.CEOSFormat.ceosTypes['leaderFile'] =
# {'typeCode': 192, 'subtypeCode': [63,18,18]}
#Parsers.CEOS.CEOSFormat.ceosTypes['dataSetSummary'] =
# {'typeCode': 10, 'subtypeCode': [10,31,20]}
#Parsers.CEOS.CEOSFormat.ceosTypes['platformPositionData'] =
# {'typeCode': 30, 'subtypeCode': [10,31,20]}
#Parsers.CEOS.CEOSFormat.ceosTypes['facilityData'] =
# {'typeCode': 200, 'subtypeCode': [10,31,50]}
#Parsers.CEOS.CEOSFormat.ceosTypes['datafileDescriptor'] =
# {'typeCode': 192, 'subtypeCode':[63,18,18]}
#Parsers.CEOS.CEOSFormat.ceosTypes['signalData'] =
# {'typeCode': 10, 'subtypeCode': [50,31,20]}
#Parsers.CEOS.CEOSFormat.ceosTypes['nullFileDescriptor'] =
# {'typeCode': 192, 'subtypeCode': [192,63,18]}
logging_name = 'isce.sensor.ers'
def __init__(self):
Component.__init__(self)
self._leaderFile = None
self._imageFileList = ''
self._leaderFileList = ''
self._imageFile = None
self._orbitDir = None # Use this for Delft Orbit files
self._orbitFile = None # Use this for PDS Orbit files for now
self._orbitType = None
self.frameList = []
self.output = None
self.descriptionOfVariables = {}
self.dictionaryOfVariables = {
'ORBIT_TYPE': ['self._orbitType','str','mandatory'],
'ORBIT_DIRECTORY': ['self._orbitDir','str','optional'],
'ORBIT_FILE': ['self._orbitFile','str','optional'],
'LEADERFILE': ['self._leaderFileList','str','mandatory'],
'IMAGEFILE': ['self._imageFileList','str','mandatory'],
'OUTPUT': ['self.output','str','optional']}
self.frame = Frame()
self.frame.configure()
# Constants are from
# J. J. Mohr and S. N. Madsen. Geometric calibration of ERS satellite
# SAR images. IEEE T. Geosci. Remote, 39(4):842-850, Apr. 2001.
self.constants = {'polarization': 'VV',
'antennaLength': 10,
'lookDirection': 'RIGHT',
'chirpPulseBandwidth': 15.50829e6,
'rangeSamplingRate': 18.962468e6,
'delayTime':6.622e-6,
'iBias': 15.5,
'qBias': 15.5}
return None
def getFrame(self):
return self.frame
def parse(self):
self.leaderFile = LeaderFile(file=self._leaderFile)
self.leaderFile.parse()
self.imageFile = ImageFile(self)
self.imageFile.parse()
self.populateMetadata()
def populateMetadata(self):
"""
Create the appropriate metadata objects from our CEOSFormat metadata
"""
self._populatePlatform()
self._populateInstrument()
self._populateFrame()
if (self._orbitType == 'ODR'):
self._populateDelftOrbits()
elif (self._orbitType == 'PRC'):
self._populatePRCOrbits()
elif (self._orbitType == 'PDS'):
self._populatePDSOrbits()
else:
self._populateHeaderOrbit()
def _populatePlatform(self):
"""
Populate the platform object with metadata
"""
platform = self.frame.getInstrument().getPlatform()
platform.setMission(self.leaderFile.sceneHeaderRecord.metadata[
'Sensor platform mission identifier'])
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPointingDirection(-1)
platform.setPlanet(Planet('Earth'))
def _populateInstrument(self):
"""Populate the instrument object with metadata"""
instrument = self.frame.getInstrument()
pri = self.imageFile.firstPri
rangeSamplingRate = self.constants['rangeSamplingRate']
#rangeSamplingRate = self.leaderFile.sceneHeaderRecord.metadata[
# 'Range sampling rate']*1e6
rangePixelSize = Const.c/(2.0*rangeSamplingRate)
pulseInterval = 4.0/rangeSamplingRate*(pri+2.0)
prf = 1.0/pulseInterval
instrument.setRadarWavelength(
self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength'])
instrument.setIncidenceAngle(
self.leaderFile.sceneHeaderRecord.metadata[
'Incidence angle at scene centre'])
instrument.setPulseRepetitionFrequency(prf)
instrument.setRangeSamplingRate(rangeSamplingRate)
instrument.setRangePixelSize(rangePixelSize)
instrument.setPulseLength(self.leaderFile.sceneHeaderRecord.metadata[
'Range pulse length']*1e-6)
instrument.setChirpSlope(self.constants['chirpPulseBandwidth']/
(self.leaderFile.sceneHeaderRecord.metadata['Range pulse length']*
1e-6))
instrument.setInPhaseValue(self.constants['iBias'])
instrument.setQuadratureValue(self.constants['qBias'])
def _populateFrame(self):
"""Populate the scene object with metadata"""
rangeSamplingRate = self.constants['rangeSamplingRate']
#rangeSamplingRate = self.leaderFile.sceneHeaderRecord.metadata[
# 'Range sampling rate']*1e6
rangePixelSize = Const.c/(2.0*rangeSamplingRate)
pulseInterval = 1.0/self.frame.getInstrument().getPulseRepetitionFrequency()
frame = self._decodeSceneReferenceNumber(
self.leaderFile.sceneHeaderRecord.metadata[
'Scene reference number'])
startingRange = (9*pulseInterval + self.imageFile.minSwst*4/rangeSamplingRate-self.constants['delayTime'])*Const.c/2.0
farRange = startingRange + self.imageFile.width*rangePixelSize
# Use the Scene center time to get the date, then use the ICU on board time from the image for the rest
centerLineTime = datetime.datetime.strptime(self.leaderFile.sceneHeaderRecord.metadata['Scene centre time'],"%Y%m%d%H%M%S%f")
first_line_utc = datetime.datetime(year=centerLineTime.year, month=centerLineTime.month, day=centerLineTime.day)
if(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier'] in ('CRDC_SARDPF','GTS - ERS')):
first_line_utc = first_line_utc + datetime.timedelta(milliseconds=self.imageFile.startTime)
else:
deltaSeconds = (self.imageFile.startTime - self.leaderFile.sceneHeaderRecord.metadata['Satellite encoded binary time code'])* 1/256.0
# Sometimes, the ICU on board clock is corrupt, if the time suggested by the on board clock is more than
# 5 days from the satellite clock time, assume its bogus and use the low-precision scene centre time
if (math.fabs(deltaSeconds) > 5*86400):
self.logger.warn("ICU on board time appears to be corrupt, resorting to low precision clock")
first_line_utc = centerLineTime - datetime.timedelta(microseconds=pulseInterval*(self.imageFile.length/2.0)*1e6)
else:
satelliteClockTime = datetime.datetime.strptime(self.leaderFile.sceneHeaderRecord.metadata['Satellite clock time'],"%Y%m%d%H%M%S%f")
first_line_utc = satelliteClockTime + datetime.timedelta(microseconds=int(deltaSeconds*1e6))
mid_line_utc = first_line_utc + datetime.timedelta(microseconds=pulseInterval*(self.imageFile.length/2.0)*1e6)
last_line_utc = first_line_utc + datetime.timedelta(microseconds=pulseInterval*self.imageFile.length*1e6)
self.logger.debug("Frame UTC start, mid, end times: %s %s %s" % (first_line_utc,mid_line_utc,last_line_utc))
self.frame.setFrameNumber(frame)
self.frame.setOrbitNumber(self.leaderFile.sceneHeaderRecord.metadata['Orbit number'])
self.frame.setStartingRange(startingRange)
self.frame.setFarRange(farRange)
self.frame.setProcessingFacility(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier'])
self.frame.setProcessingSystem(self.leaderFile.sceneHeaderRecord.metadata['Processing system identifier'])
self.frame.setProcessingSoftwareVersion(self.leaderFile.sceneHeaderRecord.metadata['Processing version identifier'])
self.frame.setPolarization(self.constants['polarization'])
self.frame.setNumberOfLines(self.imageFile.length)
self.frame.setNumberOfSamples(self.imageFile.width)
self.frame.setSensingStart(first_line_utc)
self.frame.setSensingMid(mid_line_utc)
self.frame.setSensingStop(last_line_utc)
def _populateHeaderOrbit(self):
"""Populate an orbit object with the header orbits"""
self.logger.info("Using Header Orbits")
orbit = self.frame.getOrbit()
orbit.setOrbitSource('Header')
orbit.setOrbitQuality('Unknown')
t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord.metadata['Year of data point'],
month=self.leaderFile.platformPositionRecord.metadata['Month of data point'],
day=self.leaderFile.platformPositionRecord.metadata['Day of data point'])
t0 = t0 + datetime.timedelta(microseconds=self.leaderFile.platformPositionRecord.metadata['Seconds of day']*1e6)
for i in range(self.leaderFile.platformPositionRecord.metadata['Number of data points']):
vec = StateVector()
deltaT = self.leaderFile.platformPositionRecord.metadata['Time interval between DATA points']
t = t0 + datetime.timedelta(microseconds=i*deltaT*1e6)
vec.setTime(t)
dataPoints = self.leaderFile.platformPositionRecord.metadata['Positional Data Points'][i]
vec.setPosition([dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z']])
vec.setVelocity([dataPoints['Velocity vector X'], dataPoints['Velocity vector Y'], dataPoints['Velocity vector Z']])
orbit.addStateVector(vec)
def _populateDelftOrbits(self):
"""Populate an orbit object with the Delft orbits"""
from isceobj.Orbit.ODR import ODR, Arclist
self.logger.info("Using Delft Orbits")
arclist = Arclist(os.path.join(self._orbitDir,'arclist'))
arclist.parse()
orbitFile = arclist.getOrbitFile(self.frame.getSensingStart())
odr = ODR(file=os.path.join(self._orbitDir,orbitFile))
#jng it seem that for this tipe of orbit points are separated by 60 sec. In ODR at least 9 state vectors are needed to compute the velocities. add
# extra time before and after to allow interpolation, but do not do it for all data points. too slow
startTimePreInterp = self.frame.getSensingStart() - datetime.timedelta(minutes=60)
stopTimePreInterp = self.frame.getSensingStop() + datetime.timedelta(minutes=60)
odr.parseHeader(startTimePreInterp,stopTimePreInterp)
startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime))
orbit = odr.trimOrbit(startTime,stopTime)
self.frame.setOrbit(orbit)
def _populatePRCOrbits(self):
"""Populate an orbit object the D-PAF PRC orbits"""
from isceobj.Orbit.PRC import PRC, Arclist
self.logger.info("Using PRC Orbits")
arclist = Arclist(os.path.join(self._orbitDir,'arclist'))
arclist.parse()
orbitFile = arclist.getOrbitFile(self.frame.getSensingStart())
self.logger.debug("Using file %s" % (orbitFile))
prc = PRC(file=os.path.join(self._orbitDir,orbitFile))
prc.parse()
startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime))
fullOrbit = prc.getOrbit()
orbit = fullOrbit.trimOrbit(startTime,stopTime)
self.frame.setOrbit(orbit)
def _populatePDSOrbits(self):
"""
Populate an orbit object using the ERS-2 PDS format
"""
from isceobj.Orbit.PDS import PDS
self.logger.info("Using PDS Orbits")
pds = PDS(file=self._orbitFile)
pds.parse()
startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime))
fullOrbit = pds.getOrbit()
orbit = fullOrbit.trimOrbit(startTime,stopTime)
self.frame.setOrbit(orbit)
def extractImage(self):
import array
import math
# just in case there was only one image and it was passed as a str instead of a list with only one element
if(isinstance(self._imageFileList,str)):
self._imageFileList = [self._imageFileList]
self._leaderFileList = [self._leaderFileList]
if(len(self._imageFileList) != len(self._leaderFileList)):
self.logger.error("Number of leader files different from number of image files.")
raise Exception
self.frameList = []
for i in range(len(self._imageFileList)):
appendStr = "_" + str(i)
#if only one file don't change the name
if(len(self._imageFileList) == 1):
appendStr = ''
self.frame = Frame()
self.frame.configure()
self._leaderFile = self._leaderFileList[i]
self._imageFile = self._imageFileList[i]
self.leaderFile = LeaderFile(file=self._leaderFile)
self.leaderFile.parse()
self.imageFile = ImageFile(self)
try:
outputNow = self.output + appendStr
out = open(outputNow,'wb')
except IOError as strerr:
self.logger.error("IOError: %s" % strerr)
return
self.imageFile.extractImage(output=out)
out.close()
rawImage = isceobj.createRawImage()
rawImage.setByteOrder('l')
rawImage.setAccessMode('read')
rawImage.setFilename(outputNow)
rawImage.setWidth(self.imageFile.width)
rawImage.setXmin(0)
rawImage.setXmax(self.imageFile.width)
self.frame.setImage(rawImage)
self.populateMetadata()
self.frameList.append(self.frame)
#jng Howard Z at this point adjusts the sampling starting time for imagery generated from CRDC_SARDPF facility.
# for now create the orbit aux file based in starting time and prf
prf = self.frame.getInstrument().getPulseRepetitionFrequency()
senStart = self.frame.getSensingStart()
numPulses = int(math.ceil(DTU.timeDeltaToSeconds(self.frame.getSensingStop()-senStart)*prf))
# the aux files has two entries per line. day of the year and microseconds in the day
musec0 = (senStart.hour*3600 + senStart.minute*60 + senStart.second)*10**6 + senStart.microsecond
maxMusec = (24*3600)*10**6#use it to check if we went across a day. very rare
day0 = (datetime.datetime(senStart.year,senStart.month,senStart.day) - datetime.datetime(senStart.year,1,1)).days + 1
outputArray = array.array('d',[0]*2*numPulses)
self.frame.auxFile = outputNow + '.aux'
fp = open(self.frame.auxFile,'wb')
j = -1
for i1 in range(numPulses):
j += 1
musec = round((j/prf)*10**6) + musec0
if musec >= maxMusec:
day0 += 1
musec0 = musec%maxMusec
musec = musec0
j = 0
outputArray[2*i1] = day0
outputArray[2*i1+1] = musec
outputArray.tofile(fp)
fp.close()
tk = Track()
if(len(self._imageFileList) > 1):
self.frame = tk.combineFrames(self.output,self.frameList)
for i in range(len(self._imageFileList)):
try:
os.remove(self.output + "_" + str(i))
except OSError:
print("Error. Cannot remove temporary file",self.output + "_" + str(i))
raise OSError
def _decodeSceneReferenceNumber(self,referenceNumber):
frameNumber = referenceNumber.split('=')
if (len(frameNumber) > 2):
frameNumber = frameNumber[2].strip()
else:
frameNumber = frameNumber[0]
return frameNumber
class Risat1_SLC(Sensor):
"""
Code to read CEOSFormat leader files for Risat-1 SAR data.
"""
family = "risat1"
logging_name = 'isce.sensor.Risat1'
parameter_list = (IMAGEFILE, LEADERFILE, METAFILE,
DATATYPE) + Sensor.parameter_list
@logged
def __init__(self, name=''):
super().__init__(family=self.__class__.family, name=name)
self.imageFile = None
self.leaderFile = None
#####Specific doppler functions for RISAT1
self.doppler_coeff = None
self.azfmrate_coeff = None
self.lineDirection = None
self.pixelDirection = None
self.frame = Frame()
self.frame.configure()
self.constants = {
'antennaLength': 6,
}
self.TxPolMap = {
1: 'V',
2: 'H',
3: 'L',
4: 'R',
}
self.RxPolMap = {
1: 'V',
2: 'H',
}
def getFrame(self):
return self.frame
def parse(self):
self.leaderFile = LeaderFile(self, file=self._leaderFile)
self.leaderFile.parse()
self.imageFile = ImageFile(self, file=self._imageFile)
self.imageFile.parse()
self.populateMetadata()
def populateMetadata(self):
"""
Create the appropriate metadata objects from our CEOSFormat metadata
"""
frame = self._decodeSceneReferenceNumber(
self.leaderFile.sceneHeaderRecord.
metadata['Scene reference number'])
try:
rangePixelSize = Const.c / (2 * self.leaderFile.sceneHeaderRecord.
metadata['Range sampling rate'])
except ZeroDivisionError:
rangePixelSize = 0
print(
'Average terrain height: ', 1000 * self.leaderFile.
sceneHeaderRecord.metadata['Average terrain height in km'])
ins = self.frame.getInstrument()
platform = ins.getPlatform()
platform.setMission(self.leaderFile.sceneHeaderRecord.
metadata['Sensor platform mission identifier'])
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPlanet(Planet(pname='Earth'))
ins.setRadarWavelength(
self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength'])
ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord.
metadata['Incidence angle at scene centre'])
self.frame.getInstrument().setPulseRepetitionFrequency(
self.leaderFile.sceneHeaderRecord.
metadata['Pulse Repetition Frequency'])
ins.setRangePixelSize(rangePixelSize)
ins.setRangeSamplingRate(
self.leaderFile.sceneHeaderRecord.metadata['Range sampling rate'])
ins.setPulseLength(
self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'])
chirpPulseBandwidth = self.leaderFile.processingRecord.metadata[
'Pulse bandwidth code'] * 1e4
ins.setChirpSlope(
chirpPulseBandwidth /
self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'])
ins.setInPhaseValue(0.0)
ins.setQuadratureValue(0.0)
self.lineDirection = self.leaderFile.sceneHeaderRecord.metadata[
'Time direction indicator along line direction'].strip()
self.pixelDirection = self.leaderFile.sceneHeaderRecord.metadata[
'Time direction indicator along pixel direction'].strip()
######RISAT-1 sensor orientation convention is opposite to ours
lookSide = self.leaderFile.processingRecord.metadata[
'Sensor orientation']
if lookSide == 'RIGHT':
platform.setPointingDirection(1)
elif lookSide == 'LEFT':
platform.setPointingDirection(-1)
else:
raise Exception('Unknown look side')
print('Leader file look side: ', lookSide)
self.frame.setFrameNumber(frame)
self.frame.setOrbitNumber(
self.leaderFile.sceneHeaderRecord.metadata['Orbit number'])
self.frame.setProcessingFacility(
self.leaderFile.sceneHeaderRecord.
metadata['Processing facility identifier'])
self.frame.setProcessingSystem(
self.leaderFile.sceneHeaderRecord.
metadata['Processing system identifier'])
self.frame.setProcessingSoftwareVersion(
self.leaderFile.sceneHeaderRecord.
metadata['Processing version identifier'])
self.frame.setNumberOfLines(
self.imageFile.imageFDR.metadata['Number of lines per data set'])
self.frame.setNumberOfSamples(
self.imageFile.imageFDR.
metadata['Number of pixels per line per SAR channel'])
######
self.frame.getOrbit().setOrbitSource('Header')
self.frame.getOrbit().setOrbitQuality(
self.leaderFile.platformPositionRecord.
metadata['Orbital elements designator'])
t0 = datetime.datetime(year=2000 +
self.leaderFile.platformPositionRecord.
metadata['Year of data point'],
month=self.leaderFile.platformPositionRecord.
metadata['Month of data point'],
day=self.leaderFile.platformPositionRecord.
metadata['Day of data point'])
t0 = t0 + datetime.timedelta(
seconds=self.leaderFile.platformPositionRecord.
metadata['Seconds of day'])
#####Read in orbit in inertial coordinates
orb = Orbit()
deltaT = self.leaderFile.platformPositionRecord.metadata[
'Time interval between DATA points']
numPts = self.leaderFile.platformPositionRecord.metadata[
'Number of data points']
for i in range(numPts):
vec = StateVector()
t = t0 + datetime.timedelta(seconds=i * deltaT)
vec.setTime(t)
dataPoints = self.leaderFile.platformPositionRecord.metadata[
'Positional Data Points'][i]
pos = [
dataPoints['Position vector X'],
dataPoints['Position vector Y'],
dataPoints['Position vector Z']
]
vel = [
dataPoints['Velocity vector X'],
dataPoints['Velocity vector Y'],
dataPoints['Velocity vector Z']
]
vec.setPosition(pos)
vec.setVelocity(vel)
orb.addStateVector(vec)
#####Convert orbits from ECI to ECR frame
t0 = orb._stateVectors[0]._time
ang = self.leaderFile.platformPositionRecord.metadata[
'Greenwich mean hour angle']
cOrb = ECI2ECR(orb, GAST=ang, epoch=t0)
iOrb = cOrb.convert()
#####Extend the orbits by a few points
#####Expect large azimuth shifts - absolutely needed
#####Since CEOS contains state vectors that barely covers scene extent
planet = self.frame.instrument.platform.planet
orbExt = OrbitExtender()
orbExt.configure()
orbExt._newPoints = 4
newOrb = orbExt.extendOrbit(iOrb)
orb = self.frame.getOrbit()
for sv in newOrb:
orb.addStateVector(sv)
self.doppler_coeff = [
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency centroid constant term'],
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency centroid linear term'],
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency centroid quadratic term']
]
self.azfmrate_coeff = [
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency rate constant term'],
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency rate linear term'],
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency rate quadratic term']
]
def extractImage(self):
import isceobj
if (self.imageFile is None) or (self.leaderFile is None):
self.parse()
try:
out = open(self.output, 'wb')
except IOError as strerr:
self.logger.error("IOError: %s" % strerr)
self.imageFile.extractImage(output=out, dtype=self._dataType)
out.close()
self.frame.setSensingStart(self.imageFile.sensingStart)
self.frame.setSensingStop(self.imageFile.sensingStop)
sensingMid = self.imageFile.sensingStart + datetime.timedelta(
seconds=0.5 * (self.imageFile.sensingStop -
self.imageFile.sensingStart).total_seconds())
self.frame.setSensingMid(sensingMid)
self.frame.setStartingRange(self.imageFile.nearRange)
self.frame.setFarRange(self.imageFile.farRange)
# self.doppler_coeff = self.imageFile.dopplerCoeff
self.frame.getInstrument().setPulseRepetitionFrequency(
self.imageFile.prf)
pol = self.TxPolMap[int(
self.imageFile.polarization[0])] + self.TxPolMap[int(
self.imageFile.polarization[1])]
self.frame.setPolarization(pol)
rawImage = isceobj.createSlcImage()
rawImage.setByteOrder('l')
rawImage.setAccessMode('read')
rawImage.setFilename(self.output)
rawImage.setWidth(self.imageFile.width)
rawImage.setXmin(0)
rawImage.setXmax(self.imageFile.width)
rawImage.renderHdr()
self.frame.setImage(rawImage)
return
def extractDoppler(self):
'''
Evaluate the doppler polynomial and return the average value for now.
'''
####For insarApp
quadratic = {}
quadratic['a'] = self.doppler_coeff[0] / self.frame.getInstrument(
).getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
###For roiApp
###More accurate
self.frame._dopplerVsPixel = self.doppler_coeff
return quadratic
def _decodeSceneReferenceNumber(self, referenceNumber):
return referenceNumber
class ALOS2(Sensor):
"""
Code to read CEOSFormat leader files for ALOS2 SLC data.
"""
family = 'alos2'
parameter_list = (WAVELENGTH, LEADERFILE,
IMAGEFILE) + Sensor.parameter_list
fsampConst = {
104: 1.047915957140240E+08,
52: 5.239579785701190E+07,
34: 3.493053190467460E+07,
17: 1.746526595233730E+07
}
#Orbital Elements (Quality) Designator
#ALOS-2/PALSAR-2 Level 1.1/1.5/2.1/3.1 CEOS SAR Product Format Description
#PALSAR-2_xx_Format_CEOS_E_r.pdf
orbitElementsDesignator = {
'0': 'preliminary',
'1': 'decision',
'2': 'high precision'
}
def __init__(self, name=''):
super().__init__(family=self.__class__.family, name=name)
self.leaderFile = None
self.imageFile = None
#####Soecific doppler functions for ALOS2
self.doppler_coeff = None
self.azfmrate_coeff = None
self.lineDirection = None
self.pixelDirection = None
self.frame = Frame()
self.frame.configure()
self.constants = {'polarization': 'HH', 'antennaLength': 10}
def getFrame(self):
return self.frame
def parse(self):
self.leaderFile = LeaderFile(self, file=self._leaderFile)
self.leaderFile.parse()
self.imageFile = ImageFile(self, file=self._imageFile)
self.imageFile.parse()
self.populateMetadata()
def populateMetadata(self):
"""
Create the appropriate metadata objects from our CEOSFormat metadata
"""
frame = self._decodeSceneReferenceNumber(
self.leaderFile.sceneHeaderRecord.
metadata['Scene reference number'])
fsamplookup = int(self.leaderFile.sceneHeaderRecord.
metadata['Range sampling rate in MHz'])
rangePixelSize = Const.c / (2 * self.fsampConst[fsamplookup])
ins = self.frame.getInstrument()
platform = ins.getPlatform()
platform.setMission(self.leaderFile.sceneHeaderRecord.
metadata['Sensor platform mission identifier'])
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPointingDirection(1)
platform.setPlanet(Planet(pname='Earth'))
if self.wavelength:
ins.setRadarWavelength(float(self.wavelength))
# print('ins.radarWavelength = ', ins.getRadarWavelength(),
# type(ins.getRadarWavelength()))
else:
ins.setRadarWavelength(
self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength'])
ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord.
metadata['Incidence angle at scene centre'])
self.frame.getInstrument().setPulseRepetitionFrequency(
self.leaderFile.sceneHeaderRecord.
metadata['Pulse Repetition Frequency in mHz'] * 1.0e-3)
ins.setRangePixelSize(rangePixelSize)
ins.setRangeSamplingRate(self.fsampConst[fsamplookup])
ins.setPulseLength(self.leaderFile.sceneHeaderRecord.
metadata['Range pulse length in microsec'] * 1.0e-6)
chirpSlope = self.leaderFile.sceneHeaderRecord.metadata[
'Nominal range pulse (chirp) amplitude coefficient linear term']
chirpPulseBandwidth = abs(
chirpSlope * self.leaderFile.sceneHeaderRecord.
metadata['Range pulse length in microsec'] * 1.0e-6)
ins.setChirpSlope(chirpSlope)
ins.setInPhaseValue(7.5)
ins.setQuadratureValue(7.5)
self.lineDirection = self.leaderFile.sceneHeaderRecord.metadata[
'Time direction indicator along line direction'].strip()
self.pixelDirection = self.leaderFile.sceneHeaderRecord.metadata[
'Time direction indicator along pixel direction'].strip()
######ALOS2 includes this information in clock angle
clockAngle = self.leaderFile.sceneHeaderRecord.metadata[
'Sensor clock angle']
if clockAngle == 90.0:
platform.setPointingDirection(-1)
elif clockAngle == -90.0:
platform.setPointingDirection(1)
else:
raise Exception(
'Unknown look side. Clock Angle = {0}'.format(clockAngle))
# print(self.leaderFile.sceneHeaderRecord.metadata["Sensor ID and mode of operation for this channel"])
self.frame.setFrameNumber(frame)
self.frame.setOrbitNumber(
self.leaderFile.sceneHeaderRecord.metadata['Orbit number'])
self.frame.setProcessingFacility(
self.leaderFile.sceneHeaderRecord.
metadata['Processing facility identifier'])
self.frame.setProcessingSystem(
self.leaderFile.sceneHeaderRecord.
metadata['Processing system identifier'])
self.frame.setProcessingSoftwareVersion(
self.leaderFile.sceneHeaderRecord.
metadata['Processing version identifier'])
self.frame.setPolarization(self.constants['polarization'])
self.frame.setNumberOfLines(
self.imageFile.imageFDR.metadata['Number of lines per data set'])
self.frame.setNumberOfSamples(
self.imageFile.imageFDR.
metadata['Number of pixels per line per SAR channel'])
######
orb = self.frame.getOrbit()
orb.setOrbitSource('Header')
orb.setOrbitQuality(self.orbitElementsDesignator[
self.leaderFile.platformPositionRecord.
metadata['Orbital elements designator']])
t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord.
metadata['Year of data point'],
month=self.leaderFile.platformPositionRecord.
metadata['Month of data point'],
day=self.leaderFile.platformPositionRecord.
metadata['Day of data point'])
t0 = t0 + datetime.timedelta(
seconds=self.leaderFile.platformPositionRecord.
metadata['Seconds of day'])
#####Read in orbit in inertial coordinates
deltaT = self.leaderFile.platformPositionRecord.metadata[
'Time interval between data points']
numPts = self.leaderFile.platformPositionRecord.metadata[
'Number of data points']
orb = self.frame.getOrbit()
for i in range(numPts):
vec = StateVector()
t = t0 + datetime.timedelta(seconds=i * deltaT)
vec.setTime(t)
dataPoints = self.leaderFile.platformPositionRecord.metadata[
'Positional Data Points'][i]
pos = [
dataPoints['Position vector X'],
dataPoints['Position vector Y'],
dataPoints['Position vector Z']
]
vel = [
dataPoints['Velocity vector X'],
dataPoints['Velocity vector Y'],
dataPoints['Velocity vector Z']
]
vec.setPosition(pos)
vec.setVelocity(vel)
orb.addStateVector(vec)
self.doppler_coeff = [
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency centroid constant term'],
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency centroid linear term'],
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency centroid quadratic term']
]
self.azfmrate_coeff = [
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency rate constant term'],
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency rate linear term'],
self.leaderFile.sceneHeaderRecord.
metadata['Cross track Doppler frequency rate quadratic term']
]
# print('Terrain height: ', self.leaderFile.sceneHeaderRecord.metadata['Average terrain ellipsoid height'])
def extractImage(self):
import isceobj
if (self.imageFile is None) or (self.leaderFile is None):
self.parse()
try:
out = open(self.output, 'wb')
except IOError as strerr:
self.logger.error("IOError: %s" % strerr)
self.imageFile.extractImage(output=out)
out.close()
# rangeGate = self.leaderFile.sceneHeaderRecord.metadata['Range gate delay in microsec']*1e-6
# delt = datetime.timedelta(seconds=rangeGate)
delt = datetime.timedelta(seconds=0.0)
self.frame.setSensingStart(self.imageFile.sensingStart + delt)
self.frame.setSensingStop(self.imageFile.sensingStop + delt)
sensingMid = self.imageFile.sensingStart + datetime.timedelta(
seconds=0.5 * (self.imageFile.sensingStop -
self.imageFile.sensingStart).total_seconds()) + delt
self.frame.setSensingMid(sensingMid)
self.frame.setStartingRange(self.imageFile.nearRange)
self.frame.getInstrument().setPulseRepetitionFrequency(
self.imageFile.prf)
pixelSize = self.frame.getInstrument().getRangePixelSize()
farRange = self.imageFile.nearRange + (pixelSize -
1) * self.imageFile.width
self.frame.setFarRange(farRange)
rawImage = isceobj.createSlcImage()
rawImage.setByteOrder('l')
rawImage.setAccessMode('read')
rawImage.setFilename(self.output)
rawImage.setWidth(self.imageFile.width)
rawImage.setXmin(0)
rawImage.setXmax(self.imageFile.width)
rawImage.renderHdr()
self.frame.setImage(rawImage)
return
def extractDoppler(self):
'''
Evaluate the doppler polynomial and return the average value for now.
'''
midwidth = self.frame.getNumberOfSamples() / 2.0
dop = 0.0
prod = 1.0
for ind, kk in enumerate(self.doppler_coeff):
dop += kk * prod
prod *= midwidth
print('Average Doppler: {0}'.format(dop))
####For insarApp
quadratic = {}
quadratic['a'] = dop / self.frame.getInstrument(
).getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp
####More accurate
####CEOS already provides function vs pixel
self.frame._dopplerVsPixel = self.doppler_coeff
return quadratic
def _decodeSceneReferenceNumber(self, referenceNumber):
return referenceNumber
class EnviSAT_SLC(Sensor):
parameter_list = (ORBIT_DIRECTORY, ORBITFILE, INSTRUMENTFILE,
INSTRUMENT_DIRECTORY, IMAGEFILE) + Sensor.parameter_list
"""
A Class for parsing EnviSAT instrument and imagery files
"""
family = 'envisat'
def __init__(self, family='', name=''):
super(EnviSAT_SLC,
self).__init__(family if family else self.__class__.family,
name=name)
self._imageFile = None
self._instrumentFileData = None
self._imageryFileData = None
self.dopplerRangeTime = None
self.rangeRefTime = None
self.logger = logging.getLogger("isce.sensor.EnviSAT_SLC")
self.frame = None
self.frameList = []
self.constants = {'antennaLength': 10.0, 'iBias': 128, 'qBias': 128}
def getFrame(self):
return self.frame
def parse(self):
"""
Parse both imagery and instrument files and create
objects representing the platform, instrument and scene
"""
self.frame = Frame()
self.frame.configure()
self._imageFile = ImageryFile(fileName=self._imageFileName)
self._imageryFileData = self._imageFile.parse()
if self.instrumentFile in [None, '']:
self.findInstrumentFile()
instrumentFileParser = InstrumentFile(fileName=self.instrumentFile)
self._instrumentFileData = instrumentFileParser.parse()
self.populateMetadata()
def populateMetadata(self):
self._populatePlatform()
self._populateInstrument()
self._populateFrame()
self._populateOrbit()
self.dopplerRangeTime = self._imageryFileData['doppler']
self.rangeRefTime = self._imageryFileData['dopplerOrigin'][0] * 1.0e-9
# print('Doppler confidence: ', 100.0 * self._imageryFileData['dopplerConfidence'][0])
def _populatePlatform(self):
"""Populate the platform object with metadata"""
platform = self.frame.getInstrument().getPlatform()
# Populate the Platform and Scene objects
platform.setMission("Envisat")
platform.setPointingDirection(-1)
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPlanet(Planet(pname="Earth"))
def _populateInstrument(self):
"""Populate the instrument object with metadata"""
instrument = self.frame.getInstrument()
rangeSampleSpacing = Const.c / (
2 * self._imageryFileData['rangeSamplingRate'])
pri = self._imageryFileData['pri']
####These shouldnt matter for SLC data since data is already focused.
txPulseLength = 512 / 19207680.000000
chirpPulseBandwidth = 16.0e6
chirpSlope = chirpPulseBandwidth / txPulseLength
instrument.setRangePixelSize(rangeSampleSpacing)
instrument.setPulseLength(txPulseLength)
#instrument.setSwath(imageryFileData['SWATH'])
instrument.setRadarFrequency(self._instrumentFileData['frequency'])
instrument.setChirpSlope(chirpSlope)
instrument.setRangeSamplingRate(
self._imageryFileData['rangeSamplingRate'])
instrument.setPulseRepetitionFrequency(1.0 / pri)
#instrument.setRangeBias(rangeBias)
instrument.setInPhaseValue(self.constants['iBias'])
instrument.setQuadratureValue(self.constants['qBias'])
def _populateFrame(self):
"""Populate the scene object with metadata"""
numberOfLines = self._imageryFileData['numLines']
numberOfSamples = self._imageryFileData['numSamples']
pri = self._imageryFileData['pri']
startingRange = Const.c * float(
self._imageryFileData['timeToFirstSample']) * 1.0e-9 / 2.0
rangeSampleSpacing = Const.c / (
2 * self._imageryFileData['rangeSamplingRate'])
farRange = startingRange + numberOfSamples * rangeSampleSpacing
first_line_utc = datetime.datetime.strptime(
self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
center_line_utc = datetime.datetime.strptime(
self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
last_line_utc = datetime.datetime.strptime(
self._imageryFileData['LAST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
centerTime = DTUtil.timeDeltaToSeconds(last_line_utc -
first_line_utc) / 2.0
center_line_utc = center_line_utc + datetime.timedelta(
microseconds=int(centerTime * 1e6))
self.frame.setStartingRange(startingRange)
self.frame.setFarRange(farRange)
self.frame.setProcessingFacility(self._imageryFileData['PROC_CENTER'])
self.frame.setProcessingSystem(self._imageryFileData['SOFTWARE_VER'])
self.frame.setTrackNumber(int(self._imageryFileData['REL_ORBIT']))
self.frame.setOrbitNumber(int(self._imageryFileData['ABS_ORBIT']))
self.frame.setPolarization(self._imageryFileData['MDS1_TX_RX_POLAR'])
self.frame.setNumberOfSamples(numberOfSamples)
self.frame.setNumberOfLines(numberOfLines)
self.frame.setSensingStart(first_line_utc)
self.frame.setSensingMid(center_line_utc)
self.frame.setSensingStop(last_line_utc)
def _populateOrbit(self):
if self.orbitFile in [None, '']:
self.findOrbitFile()
dorParser = DOR(fileName=self.orbitFile)
dorParser.parse()
startTime = self.frame.getSensingStart() - datetime.timedelta(
minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.frame.setOrbit(dorParser.orbit.trimOrbit(startTime, stopTime))
def _populateImage(self, outname, width, length):
#farRange = self.frame.getStartingRange() + width*self.frame.getInstrument().getRangeSamplingRate()
# Update the NumberOfSamples and NumberOfLines in the Frame object
self.frame.setNumberOfSamples(width)
self.frame.setNumberOfLines(length)
#self.frame.setFarRange(farRange)
# Create a RawImage object
rawImage = createSlcImage()
rawImage.setFilename(outname)
rawImage.setAccessMode('read')
rawImage.setByteOrder('l')
rawImage.setXmin(0)
rawImage.setXmax(width)
rawImage.setWidth(width)
self.frame.setImage(rawImage)
def extractImage(self):
from datetime import datetime as dt
import tempfile as tf
self.parse()
width = self._imageryFileData['numSamples']
length = self._imageryFileData['numLines']
self._imageFile.extractImage(self.output, width, length)
self._populateImage(self.output, width, length)
pass
def findOrbitFile(self):
datefmt = '%Y%m%d%H%M%S'
# sensingStart = self.frame.getSensingStart()
sensingStart = datetime.datetime.strptime(
self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
outFile = None
if self.orbitDir in [None, '']:
raise Exception(
'No Envisat Orbit File or Orbit Directory specified')
try:
for fname in os.listdir(self.orbitDir):
if not os.path.isfile(os.path.join(self.orbitDir, fname)):
continue
if not fname.startswith('DOR'):
continue
fields = fname.split('_')
procdate = datetime.datetime.strptime(
fields[-6][-8:] + fields[-5], datefmt)
startdate = datetime.datetime.strptime(fields[-4] + fields[-3],
datefmt)
enddate = datetime.datetime.strptime(fields[-2] + fields[-1],
datefmt)
if (sensingStart > startdate) and (sensingStart < enddate):
outFile = os.path.join(self.orbitDir, fname)
break
except:
raise Exception(
'Error occured when trying to find orbit file in %s' %
(self.orbitDir))
if not outFile:
raise Exception('Envisat orbit file could not be found in %s' %
(self.orbitDir))
self.orbitFile = outFile
return
def findInstrumentFile(self):
datefmt = '%Y%m%d%H%M%S'
sensingStart = datetime.datetime.strptime(
self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
print('sens: ', sensingStart)
outFile = None
if self.instrumentDir in [None, '']:
raise Exception(
'No Envisat Instrument File or Instrument Directory specified')
try:
for fname in os.listdir(self.instrumentDir):
if not os.path.isfile(os.path.join(self.instrumentDir, fname)):
continue
if not fname.startswith('ASA_INS'):
continue
fields = fname.split('_')
procdate = datetime.datetime.strptime(
fields[-6][-8:] + fields[-5], datefmt)
startdate = datetime.datetime.strptime(fields[-4] + fields[-3],
datefmt)
enddate = datetime.datetime.strptime(fields[-2] + fields[-1],
datefmt)
if (sensingStart > startdate) and (sensingStart < enddate):
outFile = os.path.join(self.instrumentDir, fname)
break
except:
raise Exception(
'Error occured when trying to find instrument file in %s' %
(self.instrumentDir))
if not outFile:
raise Exception(
'Envisat instrument file could not be found in %s' %
(self.instrumentDir))
self.instrumentFile = outFile
return
def extractDoppler(self):
"""
Return the doppler centroid as defined in the ASAR file.
"""
quadratic = {}
r0 = self.frame.getStartingRange()
dr = self.frame.instrument.getRangePixelSize()
width = self.frame.getNumberOfSamples()
midr = r0 + (width / 2.0) * dr
midtime = 2 * midr / Const.c - self.rangeRefTime
fd_mid = 0.0
tpow = midtime
for kk in self.dopplerRangeTime:
fd_mid += kk * tpow
tpow *= midtime
####For insarApp
quadratic['a'] = fd_mid / self.frame.getInstrument(
).getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp
####More accurate
from isceobj.Util import Poly1D
coeffs = self.dopplerRangeTime
dr = self.frame.getInstrument().getRangePixelSize()
rref = 0.5 * Const.c * self.rangeRefTime
r0 = self.frame.getStartingRange()
norm = 0.5 * Const.c / dr
dcoeffs = []
for ind, val in enumerate(coeffs):
dcoeffs.append(val / (norm**ind))
poly = Poly1D.Poly1D()
poly.initPoly(order=len(coeffs) - 1)
poly.setMean((rref - r0) / dr - 1.0)
poly.setCoeffs(dcoeffs)
pix = np.linspace(0,
self.frame.getNumberOfSamples(),
num=len(coeffs) + 1)
evals = poly(pix)
fit = np.polyfit(pix, evals, len(coeffs) - 1)
self.frame._dopplerVsPixel = list(fit[::-1])
print('Doppler Fit: ', fit[::-1])
return quadratic
class ERS_EnviSAT_SLC(Sensor):
parameter_list = (ORBIT_TYPE,
ORBIT_DIRECTORY,
ORBITFILE,
IMAGEFILE) + Sensor.parameter_list
"""
A Class for parsing ERS instrument and imagery files (Envisat format)
"""
family = 'ers'
logging_name = 'isce.sensor.ers_envisat_slc'
def __init__(self,family='',name=''):
super(ERS_EnviSAT_SLC, self).__init__(family if family else self.__class__.family, name=name)
self._imageFile = None
#self._instrumentFileData = None #none for ERS
self._imageryFileData = None
self.dopplerRangeTime = None
self.rangeRefTime = None
self.logger = logging.getLogger("isce.sensor.ERS_EnviSAT_SLC")
self.frame = None
self.frameList = []
#NOTE: copied from ERS_SLC.py... only antennaLength used? -SH
# Constants are from
# J. J. Mohr and S. N. Madsen. Geometric calibration of ERS satellite
# SAR images. IEEE T. Geosci. Remote, 39(4):842-850, Apr. 2001.
self.constants = {'polarization': 'VV',
'antennaLength': 10,
'lookDirection': 'RIGHT',
'chirpPulseBandwidth': 15.50829e6,
'rangeSamplingRate': 18.962468e6,
'delayTime':6.622e-6,
'iBias': 15.5,
'qBias': 15.5}
def getFrame(self):
return self.frame
def parse(self):
"""
Parse both imagery and create
objects representing the platform, instrument and scene
"""
self.frame = Frame()
self.frame.configure()
self._imageFile = ImageryFile(fileName=self._imageFileName)
self._imageryFileData = self._imageFile.parse()
self.populateMetadata()
def populateMetadata(self):
self._populatePlatform()
self._populateInstrument()
self._populateFrame()
#self._populateOrbit()
if (self._orbitType == 'ODR'):
self._populateDelftOrbits()
elif (self._orbitType == 'PRC'):
self._populatePRCOrbits()
elif (self._orbitType == 'PDS'):
self._populatePDSOrbits()
#else:
# self._populateHeaderOrbit() #NOTE: No leader file
#NOTE: remove?
self.dopplerRangeTime = self._imageryFileData['doppler']
self.rangeRefTime = self._imageryFileData['dopplerOrigin'][0] * 1.0e-9
# print('Doppler confidence: ', 100.0 * self._imageryFileData['dopplerConfidence'][0])
def _populatePlatform(self):
"""Populate the platform object with metadata"""
platform = self.frame.getInstrument().getPlatform()
# Populate the Platform and Scene objects
platform.setMission("ERS")
platform.setPointingDirection(-1)
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPlanet(Planet(pname="Earth"))
def _populateInstrument(self):
"""Populate the instrument object with metadata"""
instrument = self.frame.getInstrument()
rangeSampleSpacing = Const.c/(2*self._imageryFileData['rangeSamplingRate'])
pri = self._imageryFileData['pri']
####These shouldnt matter for SLC data since data is already focused.
txPulseLength = 512 / 19207680.000000
chirpPulseBandwidth = 16.0e6
chirpSlope = chirpPulseBandwidth/txPulseLength
instrument.setRangePixelSize(rangeSampleSpacing)
instrument.setPulseLength(txPulseLength)
#instrument.setSwath(imageryFileData['SWATH'])
instrument.setRadarFrequency(self._imageryFileData['radarFrequency'])
instrument.setChirpSlope(chirpSlope)
instrument.setRangeSamplingRate(self._imageryFileData['rangeSamplingRate'])
instrument.setPulseRepetitionFrequency(1.0/pri)
#instrument.setRangeBias(rangeBias)
instrument.setInPhaseValue(self.constants['iBias'])
instrument.setQuadratureValue(self.constants['qBias'])
def _populateFrame(self):
"""Populate the scene object with metadata"""
numberOfLines = self._imageryFileData['numLines']
numberOfSamples = self._imageryFileData['numSamples']
pri = self._imageryFileData['pri']
startingRange = Const.c * float(self._imageryFileData['timeToFirstSample']) * 1.0e-9 / 2.0
rangeSampleSpacing = Const.c/(2*self._imageryFileData['rangeSamplingRate'])
farRange = startingRange + numberOfSamples*rangeSampleSpacing
first_line_utc = datetime.datetime.strptime(self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
center_line_utc = datetime.datetime.strptime(self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
last_line_utc = datetime.datetime.strptime(self._imageryFileData['LAST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
centerTime = DTUtil.timeDeltaToSeconds(last_line_utc-first_line_utc)/2.0
center_line_utc = center_line_utc + datetime.timedelta(microseconds=int(centerTime*1e6))
self.frame.setStartingRange(startingRange)
self.frame.setFarRange(farRange)
self.frame.setProcessingFacility(self._imageryFileData['PROC_CENTER'])
self.frame.setProcessingSystem(self._imageryFileData['SOFTWARE_VER'])
self.frame.setTrackNumber(int(self._imageryFileData['REL_ORBIT']))
self.frame.setOrbitNumber(int(self._imageryFileData['ABS_ORBIT']))
self.frame.setPolarization(self._imageryFileData['MDS1_TX_RX_POLAR'])
self.frame.setNumberOfSamples(numberOfSamples)
self.frame.setNumberOfLines(numberOfLines)
self.frame.setSensingStart(first_line_utc)
self.frame.setSensingMid(center_line_utc)
self.frame.setSensingStop(last_line_utc)
def _populateDelftOrbits(self):
"""Populate an orbit object with the Delft orbits"""
from isceobj.Orbit.ODR import ODR, Arclist
self.logger.info("Using Delft Orbits")
arclist = Arclist(os.path.join(self._orbitDir,'arclist'))
arclist.parse()
print(self.frame.getSensingStart())
print(arclist)
orbitFile = arclist.getOrbitFile(self.frame.getSensingStart())
#print(orbitFile)
odr = ODR(file=os.path.join(self._orbitDir,orbitFile))
startTimePreInterp = self.frame.getSensingStart() - datetime.timedelta(minutes=60)
stopTimePreInterp = self.frame.getSensingStop() + datetime.timedelta(minutes=60)
odr.parseHeader(startTimePreInterp,stopTimePreInterp)
startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime))
orbit = odr.trimOrbit(startTime,stopTime)
self.frame.setOrbit(orbit)
def _populatePRCOrbits(self):
"""Populate an orbit object the D-PAF PRC orbits"""
from isceobj.Orbit.PRC import PRC, Arclist
self.logger.info("Using PRC Orbits")
arclist = Arclist(os.path.join(self._orbitDir,'arclist'))
arclist.parse()
orbitFile = arclist.getOrbitFile(self.frame.getSensingStart())
self.logger.debug("Using file %s" % (orbitFile))
prc = PRC(file=os.path.join(self._orbitDir,orbitFile))
prc.parse()
startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime))
fullOrbit = prc.getOrbit()
orbit = fullOrbit.trimOrbit(startTime,stopTime)
self.frame.setOrbit(orbit)
def _populatePDSOrbits(self):
"""
Populate an orbit object using the ERS-2 PDS format
"""
from isceobj.Orbit.PDS import PDS
self.logger.info("Using PDS Orbits")
pds = PDS(file=self._orbitFile)
pds.parse()
startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime))
fullOrbit = pds.getOrbit()
orbit = fullOrbit.trimOrbit(startTime,stopTime)
self.frame.setOrbit(orbit)
def _populateImage(self,outname,width,length):
#farRange = self.frame.getStartingRange() + width*self.frame.getInstrument().getRangeSamplingRate()
# Update the NumberOfSamples and NumberOfLines in the Frame object
self.frame.setNumberOfSamples(width)
self.frame.setNumberOfLines(length)
#self.frame.setFarRange(farRange)
# Create a RawImage object
rawImage = createSlcImage()
rawImage.setFilename(outname)
rawImage.setAccessMode('read')
rawImage.setByteOrder('l')
rawImage.setXmin(0)
rawImage.setXmax(width)
rawImage.setWidth(width)
self.frame.setImage(rawImage)
def extractImage(self):
from datetime import datetime as dt
import tempfile as tf
self.parse()
width = self._imageryFileData['numSamples']
length = self._imageryFileData['numLines']
self._imageFile.extractImage(self.output, width, length)
self._populateImage(self.output, width, length)
pass
def extractDoppler(self):
"""
Return the doppler centroid as defined in the ASAR file.
"""
quadratic = {}
r0 = self.frame.getStartingRange()
dr = self.frame.instrument.getRangePixelSize()
width = self.frame.getNumberOfSamples()
midr = r0 + (width/2.0) * dr
midtime = 2 * midr/ Const.c - self.rangeRefTime
fd_mid = 0.0
tpow = midtime
for kk in self.dopplerRangeTime:
fd_mid += kk * tpow
tpow *= midtime
####For insarApp
quadratic['a'] = fd_mid/self.frame.getInstrument().getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp
####More accurate
from isceobj.Util import Poly1D
coeffs = self.dopplerRangeTime
dr = self.frame.getInstrument().getRangePixelSize()
rref = 0.5 * Const.c * self.rangeRefTime
r0 = self.frame.getStartingRange()
norm = 0.5*Const.c/dr
dcoeffs = []
for ind, val in enumerate(coeffs):
dcoeffs.append( val / (norm**ind))
poly = Poly1D.Poly1D()
poly.initPoly(order=len(coeffs)-1)
poly.setMean( (rref - r0)/dr - 1.0)
poly.setCoeffs(dcoeffs)
pix = np.linspace(0, self.frame.getNumberOfSamples(), num=len(coeffs)+1)
evals = poly(pix)
fit = np.polyfit(pix,evals, len(coeffs)-1)
self.frame._dopplerVsPixel = list(fit[::-1])
print('Doppler Fit: ', fit[::-1])
return quadratic
class KOMPSAT5(Component):
"""
A class representing a Level1Product meta data.
Level1Product(hdf5=h5filename) will parse the hdf5
file and produce an object with attributes for metadata.
"""
logging_name = 'isce.Sensor.KOMPSAT5'
def __init__(self):
super(KOMPSAT5,self).__init__()
self.hdf5 = None
self.output = None
self.frame = Frame()
self.frame.configure()
# Some extra processing parameters unique to CSK SLC (currently)
self.dopplerCoeffs = []
self.rangeFirstTime = None
self.rangeLastTime = None
self.rangeRefTime = None
self.refUTC = None
self.descriptionOfVariables = {}
self.dictionaryOfVariables = {'HDF5': ['self.hdf5','str','mandatory'],
'OUTPUT': ['self.output','str','optional']}
self.lookMap = {'RIGHT': -1,
'LEFT': 1}
return
def __getstate__(self):
d = dict(self.__dict__)
del d['logger']
return d
def __setstate__(self,d):
self.__dict__.update(d)
self.logger = logging.getLogger('isce.Sensor.COSMO_SkyMed_SLC')
return
def getFrame(self):
return self.frame
def parse(self):
try:
fp = h5py.File(self.hdf5,'r')
except Exception as strerr:
self.logger.error("IOError: %s" % strerr)
return None
self.populateMetadata(fp)
fp.close()
def populateMetadata(self, file):
"""
Populate our Metadata objects
"""
self._populatePlatform(file)
self._populateInstrument(file)
self._populateFrame(file)
self._populateOrbit(file)
self._populateExtras(file)
def _populatePlatform(self, file):
platform = self.frame.getInstrument().getPlatform()
platform.setMission(file.attrs['Satellite ID'])
platform.setPointingDirection(self.lookMap[file.attrs['Look Side'].decode('utf-8')])
platform.setPlanet(Planet("Earth"))
####This is an approximation for spotlight mode
####In spotlight mode, antenna length changes with azimuth position
platform.setAntennaLength(file.attrs['Antenna Length'])
try:
if file.attrs['Multi-Beam ID'].startswith('ES'):
platform.setAntennaLength(16000.0/file['S01/SBI'].attrs['Line Time Interval'])
except:
pass
def _populateInstrument(self, file):
instrument = self.frame.getInstrument()
# rangePixelSize = Const.c/(2*file['S01'].attrs['Sampling Rate'])
rangePixelSize = file['S01/SBI'].attrs['Column Spacing']
instrument.setRadarWavelength(file.attrs['Radar Wavelength'])
# instrument.setPulseRepetitionFrequency(file['S01'].attrs['PRF'])
instrument.setPulseRepetitionFrequency(1.0/file['S01/SBI'].attrs['Line Time Interval'])
instrument.setRangePixelSize(rangePixelSize)
instrument.setPulseLength(file['S01'].attrs['Range Chirp Length'])
instrument.setChirpSlope(file['S01'].attrs['Range Chirp Rate'])
# instrument.setRangeSamplingRate(file['S01'].attrs['Sampling Rate'])
instrument.setRangeSamplingRate(1.0/file['S01/SBI'].attrs['Column Time Interval'])
incangle = 0.5*(file['S01/SBI'].attrs['Far Incidence Angle'] +
file['S01/SBI'].attrs['Near Incidence Angle'])
instrument.setIncidenceAngle(incangle)
def _populateFrame(self, file):
rft = file['S01/SBI'].attrs['Zero Doppler Range First Time']
slantRange = rft*Const.c/2.0
self.frame.setStartingRange(slantRange)
referenceUTC = self._parseNanoSecondTimeStamp(file.attrs['Reference UTC'])
relStart = file['S01/SBI'].attrs['Zero Doppler Azimuth First Time']
relEnd = file['S01/SBI'].attrs['Zero Doppler Azimuth Last Time']
relMid = 0.5*(relStart + relEnd)
sensingStart = self._combineDateTime(referenceUTC, relStart)
sensingStop = self._combineDateTime(referenceUTC, relEnd)
sensingMid = self._combineDateTime(referenceUTC, relMid)
self.frame.setPassDirection(file.attrs['Orbit Direction'])
self.frame.setOrbitNumber(file.attrs['Orbit Number'])
self.frame.setProcessingFacility(file.attrs['Processing Centre'])
self.frame.setProcessingSoftwareVersion(file.attrs['L0 Software Version'])
self.frame.setPolarization(file['S01'].attrs['Polarisation'])
self.frame.setNumberOfLines(file['S01/SBI'].shape[0])
self.frame.setNumberOfSamples(file['S01/SBI'].shape[1])
self.frame.setSensingStart(sensingStart)
self.frame.setSensingMid(sensingMid)
self.frame.setSensingStop(sensingStop)
rangePixelSize = self.frame.getInstrument().getRangePixelSize()
farRange = slantRange + (self.frame.getNumberOfSamples()-1)*rangePixelSize
self.frame.setFarRange(farRange)
def _populateOrbit(self,file):
orbit = self.frame.getOrbit()
orbit.setReferenceFrame('ECR')
orbit.setOrbitSource('Header')
t0 = datetime.datetime.strptime(file.attrs['Reference UTC'].decode('utf-8'),'%Y-%m-%d %H:%M:%S.%f000')
t = file.attrs['State Vectors Times']
position = file.attrs['ECEF Satellite Position']
velocity = file.attrs['ECEF Satellite Velocity']
for i in range(len(position)):
vec = StateVector()
dt = t0 + datetime.timedelta(seconds=t[i])
vec.setTime(dt)
vec.setPosition([position[i,0],position[i,1],position[i,2]])
vec.setVelocity([velocity[i,0],velocity[i,1],velocity[i,2]])
orbit.addStateVector(vec)
def _populateExtras(self, file):
"""
Populate some of the extra fields unique to processing TSX data.
In the future, other sensors may need this information as well,
and a re-organization may be necessary.
"""
from isceobj.Doppler.Doppler import Doppler
scale = file['S01'].attrs['PRF'] * file['S01/SBI'].attrs['Line Time Interval']
self.dopplerCoeffs = file.attrs['Centroid vs Range Time Polynomial']*scale
self.rangeRefTime = file.attrs['Range Polynomial Reference Time']
self.rangeFirstTime = file['S01/SBI'].attrs['Zero Doppler Range First Time']
self.rangeLastTime = file['S01/SBI'].attrs['Zero Doppler Range Last Time']
def extractImage(self):
import os
from ctypes import cdll, c_char_p
extract_csk = cdll.LoadLibrary(os.path.dirname(__file__)+'/csk.so')
inFile_c = c_char_p(bytes(self.hdf5, 'utf-8'))
outFile_c = c_char_p(bytes(self.output, 'utf-8'))
extract_csk.extract_csk_slc(inFile_c, outFile_c)
self.parse()
slcImage = isceobj.createSlcImage()
slcImage.setFilename(self.output)
slcImage.setXmin(0)
slcImage.setXmax(self.frame.getNumberOfSamples())
slcImage.setWidth(self.frame.getNumberOfSamples())
slcImage.setAccessMode('r')
self.frame.setImage(slcImage)
def _parseNanoSecondTimeStamp(self,timestamp):
"""
Parse a date-time string with nanosecond precision and return a datetime object
"""
dateTime,nanoSeconds = timestamp.decode('utf-8').split('.')
microsec = float(nanoSeconds)*1e-3
dt = datetime.datetime.strptime(dateTime,'%Y-%m-%d %H:%M:%S')
dt = dt + datetime.timedelta(microseconds=microsec)
return dt
def _combineDateTime(self,dobj, secsstr):
'''Takes the date from dobj and time from secs to spit out a date time object.
'''
sec = float(secsstr)
dt = datetime.timedelta(seconds = sec)
return dobj + dt
def extractDoppler(self):
"""
Return the doppler centroid as defined in the HDF5 file.
"""
quadratic = {}
midtime = (self.rangeLastTime + self.rangeFirstTime)*0.5 - self.rangeRefTime
fd_mid = self.dopplerCoeffs[0] + self.dopplerCoeffs[1]*midtime + self.dopplerCoeffs[2]*midtime*midtime
quadratic['a'] = fd_mid/self.frame.getInstrument().getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
return quadratic
class 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 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 Radarsat1(Component):
"""
Code to read CEOSFormat leader files for Radarsat-1 SAR data. The tables used to create
this parser are based on document number ER-IS-EPO-GS-5902.1 from the European
Space Agency.
"""
auxLength = 50
def __init__(self):
Component.__init__(self)
self._leaderFile = None
self._imageFile = None
self._parFile = None
self.output = None
self.imageFile = None
self.leaderFile = None
#####Soecific doppler functions for RSAT1
self.doppler_ref_range = None
self.doppler_ref_azi = None
self.doppler_predict = None
self.doppler_DAR = None
self.doppler_coeff = None
self.frame = Frame()
self.frame.configure()
self.constants = {'polarization': 'HH', 'antennaLength': 15}
self.descriptionOfVariables = {}
self.dictionaryOfVariables = {
'LEADERFILE': ['self._leaderFile', 'str', 'mandatory'],
'IMAGEFILE': ['self._imageFile', 'str', 'mandatory'],
'PARFILE': ['self._parFile', 'str', 'optional'],
'OUTPUT': ['self.output', 'str', 'optional']
}
def getFrame(self):
return self.frame
def parse(self):
self.leaderFile = LeaderFile(self, file=self._leaderFile)
self.leaderFile.parse()
self.imageFile = ImageFile(self, file=self._imageFile)
self.imageFile.parse()
self.populateMetadata()
def populateMetadata(self):
"""
Create the appropriate metadata objects from our CEOSFormat metadata
"""
frame = self._decodeSceneReferenceNumber(
self.leaderFile.sceneHeaderRecord.
metadata['Scene reference number'])
try:
rangePixelSize = Const.c / (2 * self.leaderFile.sceneHeaderRecord.
metadata['Range sampling rate'] * 1e6)
except ZeroDivisionError:
rangePixelSize = 0
ins = self.frame.getInstrument()
platform = ins.getPlatform()
platform.setMission(self.leaderFile.sceneHeaderRecord.
metadata['Sensor platform mission identifier'])
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPointingDirection(-1)
platform.setPlanet(Planet('Earth'))
ins.setRadarWavelength(
self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength'])
ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord.
metadata['Incidence angle at scene centre'])
##RSAT-1 does not have PRF for raw data in leader file.
# self.frame.getInstrument().setPulseRepetitionFrequency(self.leaderFile.sceneHeaderRecord.metadata['Pulse Repetition Frequency'])
ins.setRangePixelSize(rangePixelSize)
ins.setPulseLength(
self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'] *
1e-6)
chirpPulseBandwidth = 15.50829e6 # Is this really not in the CEOSFormat Header?
ins.setChirpSlope(
chirpPulseBandwidth /
(self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'] *
1e-6))
ins.setInPhaseValue(7.5)
ins.setQuadratureValue(7.5)
self.frame.setFrameNumber(frame)
self.frame.setOrbitNumber(
self.leaderFile.sceneHeaderRecord.metadata['Orbit number'])
self.frame.setProcessingFacility(
self.leaderFile.sceneHeaderRecord.
metadata['Processing facility identifier'])
self.frame.setProcessingSystem(
self.leaderFile.sceneHeaderRecord.
metadata['Processing system identifier'])
self.frame.setProcessingSoftwareVersion(
self.leaderFile.sceneHeaderRecord.
metadata['Processing version identifier'])
self.frame.setPolarization(self.constants['polarization'])
self.frame.setNumberOfLines(
self.imageFile.imageFDR.metadata['Number of lines per data set'])
self.frame.setNumberOfSamples(
self.imageFile.imageFDR.
metadata['Number of pixels per line per SAR channel'])
self.frame.getOrbit().setOrbitSource('Header')
self.frame.getOrbit().setOrbitQuality(
self.leaderFile.platformPositionRecord.
metadata['Orbital elements designator'])
t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord.
metadata['Year of data point'],
month=self.leaderFile.platformPositionRecord.
metadata['Month of data point'],
day=self.leaderFile.platformPositionRecord.
metadata['Day of data point'])
t0 = t0 + datetime.timedelta(
seconds=self.leaderFile.platformPositionRecord.
metadata['Seconds of day'])
#####Read in orbit in inertial coordinates
orb = Orbit()
for i in range(self.leaderFile.platformPositionRecord.
metadata['Number of data points']):
vec = StateVector()
t = t0 + datetime.timedelta(
seconds=(i * self.leaderFile.platformPositionRecord.
metadata['Time interval between DATA points']))
vec.setTime(t)
dataPoints = self.leaderFile.platformPositionRecord.metadata[
'Positional Data Points'][i]
vec.setPosition([
dataPoints['Position vector X'],
dataPoints['Position vector Y'],
dataPoints['Position vector Z']
])
vec.setVelocity([
dataPoints['Velocity vector X'] / 1000.,
dataPoints['Velocity vector Y'] / 1000.,
dataPoints['Velocity vector Z'] / 1000.
])
orb.addStateVector(vec)
#####Convert orbits from ECI to ECEF frame.
convOrb = ECI2ECEF(orb, eci='ECI_TOD')
wgsorb = convOrb.convert()
orb = self.frame.getOrbit()
for sv in wgsorb:
orb.addStateVector(sv)
self.parseParFile()
def extractImage(self):
import isceobj
if (self.imageFile is None) or (self.leaderFile is None):
self.parse()
try:
out = open(self.output, 'wb')
except IOError as strerr:
self.logger.error("IOError: %s" % strerr)
self.imageFile.extractImage(output=out)
out.close()
####RSAT1 is weird. Contains all useful info in RAW data and not leader.
ins = self.frame.getInstrument()
ins.setPulseRepetitionFrequency(self.imageFile.prf)
ins.setPulseLength(self.imageFile.pulseLength)
ins.setRangeSamplingRate(self.imageFile.rangeSamplingRate)
ins.setRangePixelSize(Const.c / (2 * self.imageFile.rangeSamplingRate))
ins.setChirpSlope(self.imageFile.chirpSlope)
######
self.frame.setSensingStart(self.imageFile.sensingStart)
sensingStop = self.imageFile.sensingStart + datetime.timedelta(
seconds=((self.frame.getNumberOfLines() - 1) / self.imageFile.prf))
sensingMid = self.imageFile.sensingStart + datetime.timedelta(
seconds=0.5 *
(sensingStop - self.imageFile.sensingStart).total_seconds())
self.frame.setSensingStop(sensingStop)
self.frame.setSensingMid(sensingMid)
self.frame.setNumberOfSamples(self.imageFile.width)
self.frame.setStartingRange(self.imageFile.startingRange)
farRange = self.imageFile.startingRange + ins.getRangePixelSize(
) * self.imageFile.width * 0.5
self.frame.setFarRange(farRange)
rawImage = isceobj.createRawImage()
rawImage.setByteOrder('l')
rawImage.setAccessMode('read')
rawImage.setFilename(self.output)
rawImage.setWidth(self.imageFile.width)
rawImage.setXmin(0)
rawImage.setXmax(self.imageFile.width)
rawImage.renderHdr()
self.frame.setImage(rawImage)
def parseParFile(self):
'''Parse the par file if any is available.'''
if self._parFile not in (None, ''):
par = ParFile(self._parFile)
doppinfo = par['prep_block']['sensor']['beam'][
'DopplerCentroidParameters']
#######Selectively update some values.
#######Currently used only for doppler centroids.
self.doppler_ref_range = float(doppinfo['reference_range'])
self.doppler_ref_azi = datetime.datetime.strptime(
doppinfo['reference_date'], '%Y%m%d%H%M%S%f')
self.doppler_predict = float(doppinfo['Predict_doppler'])
self.doppler_DAR = float(doppinfo['DAR_doppler'])
coeff = doppinfo['doppler_centroid_coefficients']
rngOrder = int(coeff['number_of_coefficients_first_dimension'])
azOrder = int(coeff['number_of_coefficients_second_dimension'])
self.doppler_coeff = Polynomial(rangeOrder=rngOrder,
azimuthOrder=azOrder)
self.doppler_coeff.setMeanRange(self.doppler_ref_range)
self.doppler_coeff.setMeanAzimuth(
secondsSinceMidnight(self.doppler_ref_azi))
for ii in range(azOrder):
for jj in range(rngOrder):
key = 'a%d%d' % (ii, jj)
val = float(coeff[key])
self.doppler_coeff.setCoeff(ii, jj, val)
def extractDoppler(self):
'''
Evaluate the doppler polynomial and return the average value for now.
'''
rmin = self.frame.getStartingRange()
rmax = self.frame.getFarRange()
rmid = 0.5 * (rmin + rmax)
azmid = secondsSinceMidnight(self.frame.getSensingMid())
print(rmid, self.doppler_coeff.getMeanRange())
print(azmid, self.doppler_coeff.getMeanAzimuth())
if self.doppler_coeff is None:
raise Exception(
'ASF PARFILE was not provided. Cannot determine default doppler.'
)
dopav = self.doppler_coeff(azmid, rmid)
prf = self.frame.getInstrument().getPulseRepetitionFrequency()
quadratic = {}
quadratic['a'] = dopav / prf
quadratic['b'] = 0.
quadratic['c'] = 0.
return quadratic
def _decodeSceneReferenceNumber(self, referenceNumber):
return referenceNumber
class ALOS_SLC(Sensor):
"""
Code to read CEOSFormat leader files for ALOS SLC data.
"""
parameter_list = (WAVELENGTH,
LEADERFILE,
IMAGEFILE) + Sensor.parameter_list
family = 'alos_slc'
logging_name = 'isce.sensor.ALOS_SLC'
#Orbital Elements (Quality) Designator
#ALOS-2/PALSAR-2 Level 1.1/1.5/2.1/3.1 CEOS SAR Product Format Description
#PALSAR-2_xx_Format_CEOS_E_r.pdf
orbitElementsDesignator = {'0': 'preliminary',
'1': 'decision',
'2': 'high precision'}
def __init__(self, name=''):
super().__init__(family=self.__class__.family, name=name)
self.imageFile = None
self.leaderFile = None
# Specific doppler functions for ALOS
self.doppler_coeff = None
self.azfmrate_coeff = None
self.lineDirection = None
self.pixelDirection = None
self.frame = Frame()
self.frame.configure()
self.constants = {'antennaLength': 15}
def getFrame(self):
return self.frame
def parse(self):
self.leaderFile = LeaderFile(self, file=self._leaderFile)
self.leaderFile.parse()
self.imageFile = ImageFile(self, file=self._imageFile)
self.imageFile.parse()
self.populateMetadata()
self._populateExtras()
def populateMetadata(self):
"""
Create the appropriate metadata objects from our CEOSFormat metadata
"""
frame = self._decodeSceneReferenceNumber(self.leaderFile.sceneHeaderRecord.metadata['Scene reference number'])
fsamplookup = self.leaderFile.sceneHeaderRecord.metadata['Range sampling rate in MHz']*1.0e6
rangePixelSize = Const.c/(2*fsamplookup)
ins = self.frame.getInstrument()
platform = ins.getPlatform()
platform.setMission(self.leaderFile.sceneHeaderRecord.metadata['Sensor platform mission identifier'])
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPointingDirection(1)
platform.setPlanet(Planet(pname='Earth'))
if self.wavelength:
ins.setRadarWavelength(float(self.wavelength))
else:
ins.setRadarWavelength(self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength'])
ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord.metadata['Incidence angle at scene centre'])
self.frame.getInstrument().setPulseRepetitionFrequency(self.leaderFile.sceneHeaderRecord.metadata['Pulse Repetition Frequency in mHz']*1.0e-3)
ins.setRangePixelSize(rangePixelSize)
ins.setRangeSamplingRate(fsamplookup)
ins.setPulseLength(self.leaderFile.sceneHeaderRecord.metadata['Range pulse length in microsec']*1.0e-6)
chirpSlope = self.leaderFile.sceneHeaderRecord.metadata['Nominal range pulse (chirp) amplitude coefficient linear term']
chirpPulseBandwidth = abs(chirpSlope * self.leaderFile.sceneHeaderRecord.metadata['Range pulse length in microsec']*1.0e-6)
ins.setChirpSlope(chirpSlope)
ins.setInPhaseValue(7.5)
ins.setQuadratureValue(7.5)
self.lineDirection = self.leaderFile.sceneHeaderRecord.metadata['Time direction indicator along line direction'].strip()
self.pixelDirection = self.leaderFile.sceneHeaderRecord.metadata['Time direction indicator along pixel direction'].strip()
######ALOS includes this information in clock angle
clockAngle = self.leaderFile.sceneHeaderRecord.metadata['Sensor clock angle']
if clockAngle == 90.0:
platform.setPointingDirection(-1)
elif clockAngle == -90.0:
platform.setPointingDirection(1)
else:
raise Exception('Unknown look side. Clock Angle = {0}'.format(clockAngle))
self.frame.setFrameNumber(frame)
self.frame.setOrbitNumber(self.leaderFile.sceneHeaderRecord.metadata['Orbit number'])
self.frame.setProcessingFacility(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier'])
self.frame.setProcessingSystem(self.leaderFile.sceneHeaderRecord.metadata['Processing system identifier'])
self.frame.setProcessingSoftwareVersion(self.leaderFile.sceneHeaderRecord.metadata['Processing version identifier'])
self.frame.setNumberOfLines(self.imageFile.imageFDR.metadata['Number of lines per data set'])
self.frame.setNumberOfSamples(self.imageFile.imageFDR.metadata['Number of pixels per line per SAR channel'])
self.frame.instrument.setAzimuthPixelSize(self.leaderFile.dataQualitySummaryRecord.metadata['Azimuth resolution'])
######
orb = self.frame.getOrbit()
orb.setOrbitSource('Header')
orb.setOrbitQuality(
self.orbitElementsDesignator[
self.leaderFile.platformPositionRecord.metadata['Orbital elements designator']
]
)
t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord.metadata['Year of data point'],
month=self.leaderFile.platformPositionRecord.metadata['Month of data point'],
day=self.leaderFile.platformPositionRecord.metadata['Day of data point'])
t0 = t0 + datetime.timedelta(seconds=self.leaderFile.platformPositionRecord.metadata['Seconds of day'])
#####Read in orbit in inertial coordinates
deltaT = self.leaderFile.platformPositionRecord.metadata['Time interval between data points']
numPts = self.leaderFile.platformPositionRecord.metadata['Number of data points']
orb = self.frame.getOrbit()
for i in range(numPts):
vec = StateVector()
t = t0 + datetime.timedelta(seconds=i*deltaT)
vec.setTime(t)
dataPoints = self.leaderFile.platformPositionRecord.metadata['Positional Data Points'][i]
pos = [dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z']]
vel = [dataPoints['Velocity vector X'], dataPoints['Velocity vector Y'], dataPoints['Velocity vector Z']]
vec.setPosition(pos)
vec.setVelocity(vel)
orb.addStateVector(vec)
self.doppler_coeff = [self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid constant term'],
self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid linear term'],
self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid quadratic term']]
self.azfmrate_coeff = [self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency rate constant term'],
self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency rate linear term'],
self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency rate quadratic term']]
def _populateExtras(self):
dataset = self.leaderFile.radiometricRecord.metadata
print("Record Number: %d" % (dataset["Record Number"]))
print("First Record Subtype: %d" % (dataset["First Record Subtype"]))
print("Record Type Code: %d" % (dataset["Record Type Code"]))
print("Second Record Subtype: %d" % (dataset["Second Record Subtype"]))
print("Third Record Subtype: %d" % (dataset["Third Record Subtype"]))
print("Record Length: %d" % (dataset["Record Length"]))
print("SAR channel indicator: %d" % (dataset["SAR channel indicator"]))
print("Number of data sets: %d" % (dataset["Number of data sets"]))
numPts = dataset['Number of data sets']
for i in range(numPts):
if i > 1:
break
print('Radiometric record field: %d' % (i+1))
dataset = self.leaderFile.radiometricRecord.metadata[
'Radiometric data sets'][i]
DT11 = complex(dataset['Real part of DT 1,1'],
dataset['Imaginary part of DT 1,1'])
DT12 = complex(dataset['Real part of DT 1,2'],
dataset['Imaginary part of DT 1,2'])
DT21 = complex(dataset['Real part of DT 2,1'],
dataset['Imaginary part of DT 2,1'])
DT22 = complex(dataset['Real part of DT 2,2'],
dataset['Imaginary part of DT 2,2'])
DR11 = complex(dataset['Real part of DR 1,1'],
dataset['Imaginary part of DR 1,1'])
DR12 = complex(dataset['Real part of DR 1,2'],
dataset['Imaginary part of DR 1,2'])
DR21 = complex(dataset['Real part of DR 2,1'],
dataset['Imaginary part of DR 2,1'])
DR22 = complex(dataset['Real part of DR 2,2'],
dataset['Imaginary part of DR 2,2'])
print("Calibration factor [dB]: %f" %
(dataset["Calibration factor"]))
print('Distortion matrix Trasmission [DT11, DT12, DT21, DT22]: '
'[%s, %s, %s, %s]' %
(str(DT11), str(DT12), str(DT21), str(DT22)))
print('Distortion matrix Reception [DR11, DR12, DR21, DR22]: '
'[%s, %s, %s, %s]' %
(str(DR11), str(DR12), str(DR21), str(DR22)))
self.transmit = Distortion(DT12, DT21, DT22)
self.receive = Distortion(DR12, DR21, DR22)
self.calibrationFactor = float(
dataset['Calibration factor'])
def extractImage(self):
import isceobj
if (self.imageFile is None) or (self.leaderFile is None):
self.parse()
try:
out = open(self.output, 'wb')
except IOError as strerr:
self.logger.error("IOError: %s" % strerr)
self.imageFile.extractImage(output=out)
out.close()
self.frame.setSensingStart(self.imageFile.sensingStart)
self.frame.setSensingStop(self.imageFile.sensingStop)
sensingMid = self.imageFile.sensingStart + datetime.timedelta(seconds = 0.5* (self.imageFile.sensingStop - self.imageFile.sensingStart).total_seconds())
self.frame.setSensingMid(sensingMid)
try:
rngGate= Const.c*0.5*self.leaderFile.sceneHeaderRecord.metadata['Range gate delay in microsec']*1e-6
except:
rngGate = None
if (rngGate is None) or (rngGate == 0.0):
rngGate = self.imageFile.nearRange
self.frame.setStartingRange(rngGate)
self.frame.getInstrument().setPulseRepetitionFrequency(self.imageFile.prf)
pixelSize = self.frame.getInstrument().getRangePixelSize()
farRange = self.imageFile.nearRange + (pixelSize-1) * self.imageFile.width
self.frame.setFarRange(farRange)
self.frame.setPolarization(self.imageFile.current_polarization)
rawImage = isceobj.createSlcImage()
rawImage.setByteOrder('l')
rawImage.setAccessMode('read')
rawImage.setFilename(self.output)
rawImage.setWidth(self.imageFile.width)
rawImage.setXmin(0)
rawImage.setXmax(self.imageFile.width)
rawImage.renderHdr()
self.frame.setImage(rawImage)
return
def extractDoppler(self):
'''
Evaluate the doppler polynomial and return the average value for now.
'''
midwidth = self.frame.getNumberOfSamples() / 2.0
dop = 0.0
prod = 1.0
for ind, kk in enumerate(self.doppler_coeff):
dop += kk * prod
prod *= midwidth
print ('Average Doppler: {0}'.format(dop))
####For insarApp
quadratic = {}
quadratic['a'] = dop / self.frame.getInstrument().getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp
####More accurate
####CEOS already provides function vs pixel
self.frame._dopplerVsPixel = self.doppler_coeff
return quadratic
def _decodeSceneReferenceNumber(self,referenceNumber):
return referenceNumber
class ERS_SLC(Sensor):
family = 'ers_slc'
logging_name = 'isce.sensor.ers_slc'
parameter_list = (IMAGEFILE,
LEADERFILE,
ORBIT_TYPE,
ORBIT_DIRECTORY,
ORBIT_FILE) + Sensor.parameter_list
@logged
def __init__(self, name=''):
super().__init__(family=self.__class__.family, name=name)
self.frame = Frame()
self.frame.configure()
self.dopplerRangeTime = None
# Constants are from
# J. J. Mohr and S. N. Madsen. Geometric calibration of ERS satellite
# SAR images. IEEE T. Geosci. Remote, 39(4):842-850, Apr. 2001.
self.constants = {'polarization': 'VV',
'antennaLength': 10,
'lookDirection': 'RIGHT',
'chirpPulseBandwidth': 15.50829e6,
'rangeSamplingRate': 18.962468e6,
'delayTime':6.622e-6,
'iBias': 15.5,
'qBias': 15.5}
return None
def getFrame(self):
return self.frame
def parse(self):
self.leaderFile = LeaderFile(file=self._leaderFile)
self.leaderFile.parse()
self.imageFile = ImageFile(self)
self.imageFile.parse()
self.populateMetadata()
def populateMetadata(self):
"""
Create the appropriate metadata objects from our CEOSFormat metadata
"""
self._populatePlatform()
self._populateInstrument()
self._populateFrame()
if (self._orbitType == 'ODR'):
self._populateDelftOrbits()
elif (self._orbitType == 'PRC'):
self._populatePRCOrbits()
elif (self._orbitType == 'PDS'):
self._populatePDSOrbits()
else:
self._populateHeaderOrbit()
self._populateDoppler()
def _populatePlatform(self):
"""
Populate the platform object with metadata
"""
platform = self.frame.getInstrument().getPlatform()
platform.setMission(self.leaderFile.sceneHeaderRecord.metadata[
'Sensor platform mission identifier'])
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPointingDirection(-1)
platform.setPlanet(Planet(pname='Earth'))
def _populateInstrument(self):
"""Populate the instrument object with metadata"""
instrument = self.frame.getInstrument()
prf = self.leaderFile.sceneHeaderRecord.metadata['Pulse Repetition Frequency']
rangeSamplingRate = self.leaderFile.sceneHeaderRecord.metadata['Range sampling rate']*1.0e6
rangePixelSize = Const.c/(2.0*rangeSamplingRate)
instrument.setRadarWavelength(
self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength'])
instrument.setIncidenceAngle(
self.leaderFile.sceneHeaderRecord.metadata[
'Incidence angle at scene centre'])
instrument.setPulseRepetitionFrequency(prf)
instrument.setRangeSamplingRate(rangeSamplingRate)
instrument.setRangePixelSize(rangePixelSize)
instrument.setPulseLength(self.leaderFile.sceneHeaderRecord.metadata[
'Range pulse length']*1e-6)
instrument.setChirpSlope(self.constants['chirpPulseBandwidth']/
(self.leaderFile.sceneHeaderRecord.metadata['Range pulse length']*
1e-6))
instrument.setInPhaseValue(self.constants['iBias'])
instrument.setQuadratureValue(self.constants['qBias'])
def _populateFrame(self):
"""Populate the scene object with metadata"""
rangeSamplingRate = self.constants['rangeSamplingRate']
rangePixelSize = Const.c/(2.0*rangeSamplingRate)
pulseInterval = 1.0/self.frame.getInstrument().getPulseRepetitionFrequency()
frame = self._decodeSceneReferenceNumber(
self.leaderFile.sceneHeaderRecord.metadata[
'Scene reference number'])
prf = self.frame.instrument.getPulseRepetitionFrequency()
tau0 = self.leaderFile.sceneHeaderRecord.metadata['Zero-doppler range time of first range pixel']*1.0e-3
startingRange = tau0*Const.c/2.0
farRange = startingRange + self.imageFile.width*rangePixelSize
first_line_utc = datetime.datetime.strptime(self.leaderFile.sceneHeaderRecord.metadata['Zero-doppler azimuth time of first azimuth pixel'], "%d-%b-%Y %H:%M:%S.%f")
mid_line_utc = first_line_utc + datetime.timedelta(seconds = (self.imageFile.length-1) * 0.5 / prf)
last_line_utc = first_line_utc + datetime.timedelta(seconds = (self.imageFile.length-1)/prf)
self.logger.debug("Frame UTC start, mid, end times: %s %s %s" % (first_line_utc,mid_line_utc,last_line_utc))
self.frame.setFrameNumber(frame)
self.frame.setOrbitNumber(self.leaderFile.sceneHeaderRecord.metadata['Orbit number'])
self.frame.setStartingRange(startingRange)
self.frame.setFarRange(farRange)
self.frame.setProcessingFacility(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier'])
self.frame.setProcessingSystem(self.leaderFile.sceneHeaderRecord.metadata['Processing system identifier'])
self.frame.setProcessingSoftwareVersion(self.leaderFile.sceneHeaderRecord.metadata['Processing version identifier'])
self.frame.setPolarization(self.constants['polarization'])
self.frame.setNumberOfLines(self.imageFile.length)
self.frame.setNumberOfSamples(self.imageFile.width)
self.frame.setSensingStart(first_line_utc)
self.frame.setSensingMid(mid_line_utc)
self.frame.setSensingStop(last_line_utc)
def _populateHeaderOrbit(self):
"""Populate an orbit object with the header orbits"""
self.logger.info("Using Header Orbits")
orbit = self.frame.getOrbit()
orbit.setOrbitSource('Header')
orbit.setOrbitQuality('Unknown')
t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord.metadata['Year of data point'],
month=self.leaderFile.platformPositionRecord.metadata['Month of data point'],
day=self.leaderFile.platformPositionRecord.metadata['Day of data point'])
t0 = t0 + datetime.timedelta(microseconds=self.leaderFile.platformPositionRecord.metadata['Seconds of day']*1e6)
for i in range(self.leaderFile.platformPositionRecord.metadata['Number of data points']):
vec = StateVector()
deltaT = self.leaderFile.platformPositionRecord.metadata['Time interval between DATA points']
t = t0 + datetime.timedelta(microseconds=i*deltaT*1e6)
vec.setTime(t)
dataPoints = self.leaderFile.platformPositionRecord.metadata['Positional Data Points'][i]
vec.setPosition([dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z']])
vec.setVelocity([dataPoints['Velocity vector X'], dataPoints['Velocity vector Y'], dataPoints['Velocity vector Z']])
orbit.addStateVector(vec)
def _populateDelftOrbits(self):
"""Populate an orbit object with the Delft orbits"""
from isceobj.Orbit.ODR import ODR, Arclist
self.logger.info("Using Delft Orbits")
arclist = Arclist(os.path.join(self._orbitDir,'arclist'))
arclist.parse()
orbitFile = arclist.getOrbitFile(self.frame.getSensingStart())
odr = ODR(file=os.path.join(self._orbitDir,orbitFile))
startTimePreInterp = self.frame.getSensingStart() - datetime.timedelta(minutes=60)
stopTimePreInterp = self.frame.getSensingStop() + datetime.timedelta(minutes=60)
odr.parseHeader(startTimePreInterp,stopTimePreInterp)
startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime))
orbit = odr.trimOrbit(startTime,stopTime)
self.frame.setOrbit(orbit)
def _populatePRCOrbits(self):
"""Populate an orbit object the D-PAF PRC orbits"""
from isceobj.Orbit.PRC import PRC, Arclist
self.logger.info("Using PRC Orbits")
arclist = Arclist(os.path.join(self._orbitDir,'arclist'))
arclist.parse()
orbitFile = arclist.getOrbitFile(self.frame.getSensingStart())
self.logger.debug("Using file %s" % (orbitFile))
prc = PRC(file=os.path.join(self._orbitDir,orbitFile))
prc.parse()
startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime))
fullOrbit = prc.getOrbit()
orbit = fullOrbit.trimOrbit(startTime,stopTime)
self.frame.setOrbit(orbit)
def _populatePDSOrbits(self):
"""
Populate an orbit object using the ERS-2 PDS format
"""
from isceobj.Orbit.PDS import PDS
self.logger.info("Using PDS Orbits")
pds = PDS(file=self._orbitFile)
pds.parse()
startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime))
fullOrbit = pds.getOrbit()
orbit = fullOrbit.trimOrbit(startTime,stopTime)
self.frame.setOrbit(orbit)
def _populateDoppler(self):
'''
Extract doppler from the CEOS file.
'''
prf = self.frame.instrument.getPulseRepetitionFrequency()
#####ERS provides doppler as a function of slant range time in seconds
d0 = self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid constant term']
d1 = self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid linear term']
d2 = self.leaderFile.sceneHeaderRecord.metadata['Cross track Doppler frequency centroid quadratic term']
self.dopplerRangeTime = [d0, d1, d2]
return
def extractDoppler(self):
width = self.frame.getNumberOfSamples()
prf = self.frame.instrument.getPulseRepetitionFrequency()
midtime = 0.5*width/self.frame.instrument.getRangeSamplingRate()
fd_mid = 0.0
x = 1.0
for ind, coeff in enumerate(self.dopplerRangeTime):
fd_mid += coeff * x
x *= midtime
####For insarApp
quadratic = {}
quadratic['a'] = fd_mid / prf
quadratic['b'] = 0.0
quadratic['c'] = 0.0
###For roiApp more accurate
####Convert stuff to pixel wise coefficients
dr = self.frame.getInstrument().getRangePixelSize()
norm = 0.5*Const.c/dr
dcoeffs = []
for ind, val in enumerate(self.dopplerRangeTime):
dcoeffs.append( val / (norm**ind))
self.frame._dopplerVsPixel = dcoeffs
print('Doppler Fit: ', fit[::-1])
return quadratic
def extractImage(self):
import array
import math
self.parse()
try:
out = open(self.output, 'wb')
except:
raise Exception('Cannot open output file: %s'%(self.output))
self.imageFile.extractImage(output=out)
out.close()
rawImage = isceobj.createSlcImage()
rawImage.setByteOrder('l')
rawImage.setAccessMode('read')
rawImage.setFilename(self.output)
rawImage.setWidth(self.imageFile.width)
rawImage.setXmin(0)
rawImage.setXmax(self.imageFile.width)
self.frame.setImage(rawImage)
prf = self.frame.getInstrument().getPulseRepetitionFrequency()
senStart = self.frame.getSensingStart()
numPulses = int(math.ceil(DTU.timeDeltaToSeconds(self.frame.getSensingStop()-senStart)*prf))
musec0 = (senStart.hour*3600 + senStart.minute*60 + senStart.second)*10**6 + senStart.microsecond
maxMusec = (24*3600)*10**6#use it to check if we went across a day. very rare
day0 = (datetime.datetime(senStart.year,senStart.month,senStart.day) - datetime.datetime(senStart.year,1,1)).days + 1
outputArray = array.array('d',[0]*2*numPulses)
self.frame.auxFile = self.output + '.aux'
fp = open(self.frame.auxFile,'wb')
j = -1
for i1 in range(numPulses):
j += 1
musec = round((j/prf)*10**6) + musec0
if musec >= maxMusec:
day0 += 1
musec0 = musec%maxMusec
musec = musec0
j = 0
outputArray[2*i1] = day0
outputArray[2*i1+1] = musec
outputArray.tofile(fp)
fp.close()
def _decodeSceneReferenceNumber(self,referenceNumber):
frameNumber = referenceNumber.split('=')
if (len(frameNumber) > 2):
frameNumber = frameNumber[2].strip()
else:
frameNumber = frameNumber[0]
return frameNumber
class COSMO_SkyMed_SLC(Sensor):
"""
A class representing a Level1Product meta data.
Level1Product(hdf5=h5filename) will parse the hdf5
file and produce an object with attributes for metadata.
"""
parameter_list = (HDF5, ) + Sensor.parameter_list
logging_name = 'isce.Sensor.COSMO_SkyMed_SLC'
family = 'cosmo_skymed_slc'
def __init__(self, family='', name=''):
super(COSMO_SkyMed_SLC,
self).__init__(family if family else self.__class__.family,
name=name)
self.frame = Frame()
self.frame.configure()
# Some extra processing parameters unique to CSK SLC (currently)
self.dopplerRangeTime = []
self.dopplerAzimuthTime = []
self.azimuthRefTime = None
self.rangeRefTime = None
self.rangeFirstTime = None
self.rangeLastTime = None
self.lookMap = {'RIGHT': -1, 'LEFT': 1}
return
def __getstate__(self):
d = dict(self.__dict__)
del d['logger']
return d
def __setstate__(self, d):
self.__dict__.update(d)
self.logger = logging.getLogger('isce.Sensor.COSMO_SkyMed_SLC')
return
def getFrame(self):
return self.frame
def parse(self):
try:
fp = h5py.File(self.hdf5, 'r')
except Exception as strerr:
self.logger.error("IOError: %s" % strerr)
return None
self.populateMetadata(fp)
fp.close()
def populateMetadata(self, file):
"""
Populate our Metadata objects
"""
self._populatePlatform(file)
self._populateInstrument(file)
self._populateFrame(file)
self._populateOrbit(file)
self._populateExtras(file)
def _populatePlatform(self, file):
platform = self.frame.getInstrument().getPlatform()
platform.setMission(file.attrs['Satellite ID'])
platform.setPointingDirection(
self.lookMap[file.attrs['Look Side'].decode('utf-8')])
platform.setPlanet(Planet(pname="Earth"))
####This is an approximation for spotlight mode
####In spotlight mode, antenna length changes with azimuth position
platform.setAntennaLength(file.attrs['Antenna Length'])
try:
if file.attrs['Multi-Beam ID'].startswith('ES'):
platform.setAntennaLength(
16000.0 / file['S01/SBI'].attrs['Line Time Interval'])
except:
pass
def _populateInstrument(self, file):
instrument = self.frame.getInstrument()
# rangePixelSize = Const.c/(2*file['S01'].attrs['Sampling Rate'])
rangePixelSize = file['S01/SBI'].attrs['Column Spacing']
instrument.setRadarWavelength(file.attrs['Radar Wavelength'])
# instrument.setPulseRepetitionFrequency(file['S01'].attrs['PRF'])
instrument.setPulseRepetitionFrequency(
1.0 / file['S01/SBI'].attrs['Line Time Interval'])
instrument.setRangePixelSize(rangePixelSize)
instrument.setPulseLength(file['S01'].attrs['Range Chirp Length'])
instrument.setChirpSlope(file['S01'].attrs['Range Chirp Rate'])
# instrument.setRangeSamplingRate(file['S01'].attrs['Sampling Rate'])
instrument.setRangeSamplingRate(
1.0 / file['S01/SBI'].attrs['Column Time Interval'])
incangle = 0.5 * (file['S01/SBI'].attrs['Far Incidence Angle'] +
file['S01/SBI'].attrs['Near Incidence Angle'])
instrument.setIncidenceAngle(incangle)
def _populateFrame(self, file):
rft = file['S01/SBI'].attrs['Zero Doppler Range First Time']
slantRange = rft * Const.c / 2.0
self.frame.setStartingRange(slantRange)
referenceUTC = self._parseNanoSecondTimeStamp(
file.attrs['Reference UTC'])
relStart = file['S01/SBI'].attrs['Zero Doppler Azimuth First Time']
relEnd = file['S01/SBI'].attrs['Zero Doppler Azimuth Last Time']
relMid = 0.5 * (relStart + relEnd)
sensingStart = self._combineDateTime(referenceUTC, relStart)
sensingStop = self._combineDateTime(referenceUTC, relEnd)
sensingMid = self._combineDateTime(referenceUTC, relMid)
self.frame.setPassDirection(file.attrs['Orbit Direction'])
self.frame.setOrbitNumber(file.attrs['Orbit Number'])
self.frame.setProcessingFacility(file.attrs['Processing Centre'])
self.frame.setProcessingSoftwareVersion(
file.attrs['L0 Software Version'])
self.frame.setPolarization(file['S01'].attrs['Polarisation'])
self.frame.setNumberOfLines(file['S01/SBI'].shape[0])
self.frame.setNumberOfSamples(file['S01/SBI'].shape[1])
self.frame.setSensingStart(sensingStart)
self.frame.setSensingMid(sensingMid)
self.frame.setSensingStop(sensingStop)
rangePixelSize = self.frame.getInstrument().getRangePixelSize()
farRange = slantRange + (self.frame.getNumberOfSamples() -
1) * rangePixelSize
self.frame.setFarRange(farRange)
def _populateOrbit(self, file):
orbit = self.frame.getOrbit()
orbit.setReferenceFrame('ECR')
orbit.setOrbitSource('Header')
t0 = datetime.datetime.strptime(
file.attrs['Reference UTC'].decode('utf-8'),
'%Y-%m-%d %H:%M:%S.%f000')
t = file.attrs['State Vectors Times']
position = file.attrs['ECEF Satellite Position']
velocity = file.attrs['ECEF Satellite Velocity']
for i in range(len(position)):
vec = StateVector()
dt = t0 + datetime.timedelta(seconds=t[i])
vec.setTime(dt)
vec.setPosition([position[i, 0], position[i, 1], position[i, 2]])
vec.setVelocity([velocity[i, 0], velocity[i, 1], velocity[i, 2]])
orbit.addStateVector(vec)
def _populateExtras(self, file):
"""
Populate some of the extra fields unique to processing TSX data.
In the future, other sensors may need this information as well,
and a re-organization may be necessary.
"""
from isceobj.Doppler.Doppler import Doppler
self.dopplerRangeTime = file.attrs['Centroid vs Range Time Polynomial']
self.dopplerAzimuthTime = file.attrs[
'Centroid vs Azimuth Time Polynomial']
self.rangeRefTime = file.attrs['Range Polynomial Reference Time']
self.azimuthRefTime = file.attrs['Azimuth Polynomial Reference Time']
self.rangeFirstTime = file['S01/SBI'].attrs[
'Zero Doppler Range First Time']
self.rangeLastTime = file['S01/SBI'].attrs[
'Zero Doppler Range Last Time']
# get Doppler rate information, vs. azimuth first EJF 2015/00/05
# guessing that same scale applies as for Doppler centroid
self.dopplerRateCoeffs = file.attrs[
'Doppler Rate vs Azimuth Time Polynomial']
def extractImage(self):
import os
from ctypes import cdll, c_char_p
extract_csk = cdll.LoadLibrary(os.path.dirname(__file__) + '/csk.so')
inFile_c = c_char_p(bytes(self.hdf5, 'utf-8'))
outFile_c = c_char_p(bytes(self.output, 'utf-8'))
extract_csk.extract_csk_slc(inFile_c, outFile_c)
self.parse()
slcImage = isceobj.createSlcImage()
slcImage.setFilename(self.output)
slcImage.setXmin(0)
slcImage.setXmax(self.frame.getNumberOfSamples())
slcImage.setWidth(self.frame.getNumberOfSamples())
slcImage.setAccessMode('r')
self.frame.setImage(slcImage)
def _parseNanoSecondTimeStamp(self, timestamp):
"""
Parse a date-time string with nanosecond precision and return a datetime object
"""
dateTime, nanoSeconds = timestamp.decode('utf-8').split('.')
microsec = float(nanoSeconds) * 1e-3
dt = datetime.datetime.strptime(dateTime, '%Y-%m-%d %H:%M:%S')
dt = dt + datetime.timedelta(microseconds=microsec)
return dt
def _combineDateTime(self, dobj, secsstr):
'''Takes the date from dobj and time from secs to spit out a date time object.
'''
sec = float(secsstr)
dt = datetime.timedelta(seconds=sec)
return datetime.datetime.combine(dobj.date(), datetime.time(0, 0)) + dt
def extractDoppler(self):
"""
Return the doppler centroid as defined in the HDF5 file.
"""
import numpy as np
quadratic = {}
midtime = (self.rangeLastTime +
self.rangeFirstTime) * 0.5 - self.rangeRefTime
fd_mid = 0.0
x = 1.0
for ind, coeff in enumerate(self.dopplerRangeTime):
fd_mid += coeff * x
x *= midtime
####insarApp style
quadratic['a'] = fd_mid / self.frame.getInstrument(
).getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp more accurate
####Convert stuff to pixel wise coefficients
from isceobj.Util import Poly1D
coeffs = self.dopplerRangeTime
dr = self.frame.getInstrument().getRangePixelSize()
rref = 0.5 * Const.c * self.rangeRefTime
r0 = self.frame.getStartingRange()
norm = 0.5 * Const.c / dr
dcoeffs = []
for ind, val in enumerate(coeffs):
dcoeffs.append(val / (norm**ind))
poly = Poly1D.Poly1D()
poly.initPoly(order=len(coeffs) - 1)
poly.setMean((rref - r0) / dr - 1.0)
poly.setCoeffs(dcoeffs)
pix = np.linspace(0,
self.frame.getNumberOfSamples(),
num=len(coeffs) + 1)
evals = poly(pix)
fit = np.polyfit(pix, evals, len(coeffs) - 1)
self.frame._dopplerVsPixel = list(fit[::-1])
print('Doppler Fit: ', fit[::-1])
#EMG - 20160420 This section was introduced in the populateMetadata method by EJF in r2022
#Its pupose seems to be to set self.doppler_coeff and self.azfmrate_coeff, which don't seem
#to be used anywhere in ISCE. Need to take time to understand the need for this and consult
#with EJF.
#
## save the Doppler centroid coefficients, converting units from .h5 file
## units in the file are quadratic coefficients in Hz, Hz/sec, and Hz/(sec^2)
## ISCE expects Hz, Hz/(range sample), Hz/(range sample)^2
## note that RS2 Doppler values are estimated at time dc.dopplerCentroidReferenceTime,
## so the values might need to be adjusted for ISCE usage
## adapted from RS2 version EJF 2015/09/05
# poly = self.frame._dopplerVsPixel
# rangeSamplingRate = self.frame.getInstrument().getPulseRepetitionFrequency()
# # need to convert units
# poly[1] = poly[1]/rangeSamplingRate
# poly[2] = poly[2]/rangeSamplingRate**2
# self.doppler_coeff = poly
#
## similarly save Doppler azimuth fm rate values, converting units
## units in the file are quadratic coefficients in Hz, Hz/sec, and Hz/(sec^2)
## units are already converted below
## Guessing that ISCE expects Hz, Hz/(azimuth line), Hz/(azimuth line)^2
## note that RS2 Doppler values are estimated at time dc.dopplerRateReferenceTime,
## so the values might need to be adjusted for ISCE usage
## modified from RS2 version EJF 2015/09/05
## CSK Doppler azimuth FM rate not yet implemented in reading section, set to zero for now
#
# fmpoly = self.dopplerRateCoeffs
# # don't need to convert units
## fmpoly[1] = fmpoly[1]/rangeSamplingRate
## fmpoly[2] = fmpoly[2]/rangeSamplingRate**2
# self.azfmrate_coeff = fmpoly
#EMG - 20160420
return quadratic
class 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
