326 lines
12 KiB
Python
326 lines
12 KiB
Python
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#!/usr/bin/env python3
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#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Copyright 2013 California Institute of Technology. ALL RIGHTS RESERVED.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# United States Government Sponsorship acknowledged. This software is subject to
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# U.S. export control laws and regulations and has been classified as 'EAR99 NLR'
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# (No [Export] License Required except when exporting to an embargoed country,
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# end user, or in support of a prohibited end use). By downloading this software,
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# the user agrees to comply with all applicable U.S. export laws and regulations.
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# The user has the responsibility to obtain export licenses, or other export
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# authority as may be required before exporting this software to any 'EAR99'
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# embargoed foreign country or citizen of those countries.
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#
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# Author: Heresh Fattahi
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#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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import datetime
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import logging
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try:
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import h5py
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except ImportError:
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raise ImportError(
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"Python module h5py is required to process COSMO-SkyMed data"
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)
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import isceobj
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from isceobj.Scene.Frame import Frame
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from isceobj.Orbit.Orbit import StateVector
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from isceobj.Planet.Planet import Planet
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from isceobj.Planet.AstronomicalHandbook import Const
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from isceobj.Sensor import cosar
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from iscesys.DateTimeUtil.DateTimeUtil import DateTimeUtil as DTU
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from isceobj.Sensor import tkfunc,createAuxFile
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from iscesys.Component.Component import Component
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from isceobj.Constants import SPEED_OF_LIGHT
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HDF5 = Component.Parameter(
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'hdf5',
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public_name='HDF5',
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default=None,
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type=str,
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mandatory=True,
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intent='input',
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doc='UAVSAR slc input file in HDF5 format'
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)
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FREQUENCY = Component.Parameter(
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'frequency',
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public_name='FREQUENCY',
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default='frequencyA',
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type=str,
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mandatory=True,
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intent='input',
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doc='frequency band of the UAVSAR slc file to be processed (frequencyA or frequencyB)'
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)
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POLARIZATION = Component.Parameter(
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'polarization',
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public_name='POLARIZATION',
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default='HH',
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type=str,
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mandatory=True,
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intent='input',
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doc='polarization channel of the UAVSAR slc file to be processed'
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)
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from .Sensor import Sensor
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class UAVSAR_HDF5_SLC(Sensor):
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"""
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A class representing a Level1Product meta data.
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Level1Product(hdf5=h5filename) will parse the hdf5
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file and produce an object with attributes for metadata.
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"""
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parameter_list = (HDF5,
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FREQUENCY,
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POLARIZATION) + Sensor.parameter_list
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logging_name = 'isce.Sensor.UAVSAR_HDF5_SLC'
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family = 'uavsar_hdf5_slc'
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def __init__(self,family='',name=''):# , frequency='frequencyA', polarization='HH'):
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super(UAVSAR_HDF5_SLC,self).__init__(family if family else self.__class__.family, name=name)
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self.frame = Frame()
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self.frame.configure()
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# Some extra processing parameters unique to UAVSAR HDF5 SLC (currently)
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self.dopplerRangeTime = []
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self.dopplerAzimuthTime = []
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self.azimuthRefTime = None
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self.rangeRefTime = None
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self.rangeFirstTime = None
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self.rangeLastTime = None
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#self.frequency = frequency
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#self.polarization = polarization
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self.lookMap = {'right': -1,
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'left': 1}
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return
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def __getstate__(self):
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d = dict(self.__dict__)
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del d['logger']
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return d
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def __setstate__(self,d):
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self.__dict__.update(d)
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self.logger = logging.getLogger('isce.Sensor.UAVSAR_HDF5_SLC')
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return
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def getFrame(self):
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return self.frame
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def parse(self):
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try:
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fp = h5py.File(self.hdf5,'r')
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except Exception as strerr:
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self.logger.error("IOError: %s" % strerr)
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return None
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self.populateMetadata(fp)
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fp.close()
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def populateMetadata(self, file):
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"""
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Populate our Metadata objects
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"""
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self._populatePlatform(file)
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self._populateInstrument(file)
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self._populateFrame(file)
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self._populateOrbit(file)
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def _populatePlatform(self, file):
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platform = self.frame.getInstrument().getPlatform()
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platform.setMission(file['/science/LSAR/identification'].get('missionId')[()].decode('utf-8'))
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platform.setPointingDirection(self.lookMap[file['/science/LSAR/identification'].get('lookDirection')[()].decode('utf-8')])
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platform.setPlanet(Planet(pname="Earth"))
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# We are not using this value anywhere. Let's fix it for now.
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platform.setAntennaLength(12.0)
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def _populateInstrument(self, file):
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instrument = self.frame.getInstrument()
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rangePixelSize = file['/science/LSAR/SLC/swaths/' + self.frequency + '/slantRangeSpacing'][()]
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wvl = SPEED_OF_LIGHT/file['/science/LSAR/SLC/swaths/' + self.frequency + '/processedCenterFrequency'][()]
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instrument.setRadarWavelength(wvl)
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instrument.setPulseRepetitionFrequency(1.0/file['/science/LSAR/SLC/swaths/zeroDopplerTimeSpacing'][()])
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rangePixelSize = file['/science/LSAR/SLC/swaths/' + self.frequency + '/slantRangeSpacing'][()]
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instrument.setRangePixelSize(rangePixelSize)
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# Chrip slope and length only are used in the split spectrum workflow to compute the bandwidth.
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# Therefore fixing it to 1.0 won't breack anything
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Chirp_slope = 1.0
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rangeBandwidth = file['/science/LSAR/SLC/swaths/' + self.frequency + '/processedRangeBandwidth'][()]
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Chirp_length = rangeBandwidth/Chirp_slope
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instrument.setPulseLength(Chirp_length)
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instrument.setChirpSlope(Chirp_slope)
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rangeSamplingFrequency = SPEED_OF_LIGHT/2./rangePixelSize
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instrument.setRangeSamplingRate(rangeSamplingFrequency)
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incangle = 0.0
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instrument.setIncidenceAngle(incangle)
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def _populateFrame(self, file):
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slantRange = file['/science/LSAR/SLC/swaths/' + self.frequency + '/slantRange'][0]
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self.frame.setStartingRange(slantRange)
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referenceUTC = file['/science/LSAR/SLC/swaths/zeroDopplerTime'].attrs['units'].decode('utf-8')
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referenceUTC = referenceUTC.replace('seconds since ','')
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referenceUTC = datetime.datetime.strptime(referenceUTC,'%Y-%m-%d %H:%M:%S')
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relStart = file['/science/LSAR/SLC/swaths/zeroDopplerTime'][0]
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relEnd = file['/science/LSAR/SLC/swaths/zeroDopplerTime'][-1]
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relMid = 0.5*(relStart + relEnd)
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sensingStart = self._combineDateTime(referenceUTC, relStart)
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sensingStop = self._combineDateTime(referenceUTC, relEnd)
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sensingMid = self._combineDateTime(referenceUTC, relMid)
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self.frame.setPassDirection(file['/science/LSAR/identification'].get('orbitPassDirection')[()].decode('utf-8'))
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self.frame.setOrbitNumber(file['/science/LSAR/identification'].get('trackNumber')[()])
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self.frame.setProcessingFacility('JPL')
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self.frame.setProcessingSoftwareVersion(file['/science/LSAR/SLC/metadata/processingInformation/algorithms'].get('ISCEVersion')[()].decode('utf-8'))
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self.frame.setPolarization(self.polarization)
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self.frame.setNumberOfLines(file['/science/LSAR/SLC/swaths/' + self.frequency + '/' + self.polarization].shape[0])
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self.frame.setNumberOfSamples(file['/science/LSAR/SLC/swaths/' + self.frequency + '/' + self.polarization].shape[1])
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self.frame.setSensingStart(sensingStart)
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self.frame.setSensingMid(sensingMid)
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self.frame.setSensingStop(sensingStop)
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rangePixelSize = self.frame.instrument.rangePixelSize
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farRange = slantRange + (self.frame.getNumberOfSamples()-1)*rangePixelSize
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self.frame.setFarRange(farRange)
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def _populateOrbit(self,file):
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orbit = self.frame.getOrbit()
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orbit.setReferenceFrame('ECR')
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orbit.setOrbitSource('Header')
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referenceUTC = file['/science/LSAR/SLC/swaths/zeroDopplerTime'].attrs['units'].decode('utf-8')
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referenceUTC = referenceUTC.replace('seconds since ','')
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t0 = datetime.datetime.strptime(referenceUTC,'%Y-%m-%d %H:%M:%S')
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t = file['/science/LSAR/SLC/metadata/orbit/time']
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position = file['/science/LSAR/SLC/metadata/orbit/position']
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velocity = file['/science/LSAR/SLC/metadata/orbit/velocity']
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for i in range(len(position)):
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vec = StateVector()
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dt = t0 + datetime.timedelta(seconds=t[i])
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vec.setTime(dt)
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vec.setPosition([position[i,0],position[i,1],position[i,2]])
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vec.setVelocity([velocity[i,0],velocity[i,1],velocity[i,2]])
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orbit.addStateVector(vec)
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def extractImage(self):
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import numpy as np
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import h5py
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self.parse()
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fid = h5py.File(self.hdf5, 'r')
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ds = fid['/science/LSAR/SLC/swaths/' + self.frequency + '/' + self.polarization]
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nLines = ds.shape[0]
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with open(self.output, 'wb') as fout:
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for ii in range(nLines):
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ds[ii,:].astype(np.complex64).tofile(fout)
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fid.close()
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slcImage = isceobj.createSlcImage()
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slcImage.setFilename(self.output)
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slcImage.setXmin(0)
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slcImage.setXmax(self.frame.getNumberOfSamples())
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slcImage.setWidth(self.frame.getNumberOfSamples())
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slcImage.setAccessMode('r')
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slcImage.renderHdr()
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self.frame.setImage(slcImage)
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def _parseNanoSecondTimeStamp(self,timestamp):
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"""
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Parse a date-time string with nanosecond precision and return a datetime object
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"""
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dateTime,nanoSeconds = timestamp.decode('utf-8').split('.')
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microsec = float(nanoSeconds)*1e-3
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dt = datetime.datetime.strptime(dateTime,'%Y-%m-%d %H:%M:%S')
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dt = dt + datetime.timedelta(microseconds=microsec)
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return dt
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def _combineDateTime(self,dobj, secsstr):
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'''Takes the date from dobj and time from secs to spit out a date time object.
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'''
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sec = float(secsstr)
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dt = datetime.timedelta(seconds = sec)
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return dobj + dt
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def extractDoppler(self):
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"""
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Return the doppler centroid as defined in the HDF5 file.
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"""
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import h5py
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from scipy.interpolate import UnivariateSpline
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import numpy as np
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h5 = h5py.File(self.hdf5,'r')
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# extract the 2D LUT of Doppler and choose only one range line as the data duplicates for other range lines
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dop = h5['/science/LSAR/SLC/metadata/processingInformation/parameters/' + self.frequency + '/dopplerCentroid'][0,:]
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rng = h5['/science/LSAR/SLC/metadata/processingInformation/parameters/slantRange']
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# extract the slant range of the image grid
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imgRng = h5['/science/LSAR/SLC/swaths/' + self.frequency + '/slantRange']
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# use only part of the slant range that closely covers image ranges and ignore the rest
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ind0 = np.argmin(np.abs(rng-imgRng[0])) - 1
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ind0 = np.max([0,ind0])
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ind1 = np.argmin(np.abs(rng-imgRng[-1])) + 1
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ind1 = np.min([ind1, rng.shape[0]])
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dop = dop[ind0:ind1]
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rng = rng[ind0:ind1]
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f = UnivariateSpline(rng, dop)
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imgDop = f(imgRng)
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dr = imgRng[1]-imgRng[0]
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pix = (imgRng - imgRng[0])/dr
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fit = np.polyfit(pix, imgDop, 41)
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self.frame._dopplerVsPixel = list(fit[::-1])
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####insarApp style (doesn't get used for stripmapApp). A fixed Doppler at the middle of the scene
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quadratic = {}
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quadratic['a'] = imgDop[int(imgDop.shape[0]/2)]/self.frame.getInstrument().getPulseRepetitionFrequency()
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quadratic['b'] = 0.
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quadratic['c'] = 0.
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return quadratic
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