def extractTOWandCN0(SVprn, measData, TOWmeas, CN0meas, verbose=False):
"""
extractTOWandCN0 axtracts for a SV the TOW and CN0 values observed per signaltype
Parameters:
SVprn: the ID for this SV
measData: the measurement data from MEAS_EPOCH
TOWmeas: array of lists that contains the TOW for this PRN and per signalType
CN0meas: idem for CN0
Returns:
the signal types for this SVprn
"""
if verbose:
print(' Processing SVID = %d' % SVprn)
# find indices with data for this SVID
# print('SVprn = %s' % SVprn)
indexSVprn = sbf2stf.indicesSatellite(SVprn, measData['MEAS_SVID'],
verbose)
# print('indexSVprn = %s' % indexSVprn)
dataMeasSVprn = measData[indexSVprn]
# print('dataMeasSVprn = %s' % dataMeasSVprn)
# find indices that correspond to the signalTypes for this SVprn
signalTypesSVprn = sbf2stf.observedSignalTypes(
dataMeasSVprn['MEAS_SIGNALTYPE'], verbose)
indexSignalType = []
for index, signalType in enumerate(signalTypesSVprn):
if verbose:
print(' Treating signalType = %s (index=%d)' %
(signalType, index))
# get the observation time span and observed CN0 for this SVprn and SignalType
indexSignalType.extend(
np.array(
sbf2stf.indicesSignalType(signalType,
dataMeasSVprn['MEAS_SIGNALTYPE'],
verbose)))
TOWmeas.append(dataMeasSVprn[indexSignalType[index]]['MEAS_TOW'])
CN0meas.append(dataMeasSVprn[indexSignalType[index]]['MEAS_CN0'])
# # print last added values
if True:
print('TOWmeas[%d] = %d => %d (%d)' %
(len(TOWmeas), TOWmeas[-1][0], TOWmeas[-1][-1],
np.size(TOWmeas[-1])))
print('CN0meas[%d] = %f => %s (%d)' %
(len(CN0meas), CN0meas[-1][0], CN0meas[-1][-1],
np.size(CN0meas[-1])))
return signalTypesSVprn
def extractTOWandCN0(SVprn, measData, TOWmeas, CN0meas, verbose=False):
"""
extractTOWandCN0 axtracts for a SV the TOW and CN0 values observed per signaltype
Parameters:
SVprn: the ID for this SV
measData: the measurement data from MEAS_EPOCH
TOWmeas: array of lists that contains the TOW for this PRN and per signalType
CN0meas: idem for CN0
Returns:
the signal types for this SVprn
"""
if verbose:
print(' Processing SVID = %d' % SVprn)
# find indices with data for this SVID
# print('SVprn = %s' % SVprn)
indexSVprn = sbf2stf.indicesSatellite(SVprn, measData['MEAS_SVID'], verbose)
# print('indexSVprn = %s' % indexSVprn)
dataMeasSVprn = measData[indexSVprn]
# print('dataMeasSVprn = %s' % dataMeasSVprn)
# find indices that correspond to the signalTypes for this SVprn
signalTypesSVprn = sbf2stf.observedSignalTypes(dataMeasSVprn['MEAS_SIGNALTYPE'], verbose)
indexSignalType = []
for index, signalType in enumerate(signalTypesSVprn):
if verbose:
print(' Treating signalType = %s (index=%d)' % (signalType, index))
# get the observation time span and observed CN0 for this SVprn and SignalType
indexSignalType.extend(np.array(sbf2stf.indicesSignalType(signalType, dataMeasSVprn['MEAS_SIGNALTYPE'], verbose)))
TOWmeas.append(dataMeasSVprn[indexSignalType[index]]['MEAS_TOW'])
CN0meas.append(dataMeasSVprn[indexSignalType[index]]['MEAS_CN0'])
# # print last added values
if True:
print('TOWmeas[%d] = %d => %d (%d)' % (len(TOWmeas), TOWmeas[-1][0], TOWmeas[-1][-1], np.size(TOWmeas[-1])))
print('CN0meas[%d] = %f => %s (%d)' % (len(CN0meas), CN0meas[-1][0], CN0meas[-1][-1], np.size(CN0meas[-1])))
return signalTypesSVprn
# determine current weeknumber and subsequent date from SBF data
WkNr = int(dataMeas['MEAS_WNC'][0])
dateString = gpstime.UTCFromWT(WkNr, float(
dataMeas['MEAS_TOW'][0])).strftime("%d/%m/%Y")
if verbose:
print('WkNr = %d - dateString = %s' % (WkNr, dateString))
# correct the smoothed PR Code and work with the raw PR
dataMeas['MEAS_CODE'] = sbf2stf.removeSmoothing(
dataMeas['MEAS_CODE'], dataExtra['EXTRA_SMOOTHINGCORR'],
dataExtra['EXTRA_MPCORR'])
# print('rawPR = %s\n' % dataMeas['MEAS_CODE'])
# find list of SVIDs and SignalTypes observed
SVIDs = sbf2stf.observedSatellites(dataMeas['MEAS_SVID'], verbose)
signalTypes = sbf2stf.observedSignalTypes(dataMeas['MEAS_SIGNALTYPE'],
verbose)
# create the CN0 plots for all SVs and SignalTypes
indexSignalType = []
dataMeasSignalType = []
# storing data in arrays per SV and per signalType
measTOW = [] # TOWs with measurements
measCN0 = [] # CNO values @ measTOW
STlist = [] # list of signaltypes traversed
SVIDlist = [] # list of SVIDs traversed
# extract first TOW and CN0 arrays for all SVs and signaltypes
for SVID in SVIDs:
signalTypesSVID = extractTOWandCN0(SVID, dataMeas, measTOW, measCN0,
verbose)
for SVID in SVIDs:
print('=' * 50)
gnssSyst, gnssSystShort, gnssPRN = mSSN.svPRN(SVID)
print('SVID = %d - %s - %s%d' % (SVID, gnssSyst, gnssSystShort, gnssPRN))
indexSVID = sbf2stf.indicesSatellite(SVID, dataMeas['MEAS_SVID'], verbose)
dataMeasSVID = dataMeas[indexSVID]
print("indexSVID = %s" % indexSVID)
# store temporaray results ONLY for inspection
nameDataMeasSVID = str(SVID) + '.csv'
print('nameDataMeasSVID = %s' % nameDataMeasSVID)
print('dataMeasSVID = %s' % dataMeasSVID)
np.savetxt(nameDataMeasSVID, dataMeasSVID, fmt='%i,%.1f,%i,%i,%i,%i,%i,%.2f,%.2f,%.2f,%.2f,%i,%i,%i')
signalTypesSVID = sbf2stf.observedSignalTypes(dataMeasSVID['MEAS_SIGNALTYPE'], verbose)
print('signalTypesSVID = %s' % signalTypesSVID)
# print("len dataMeas['MEAS_CODE'] %d" % len(dataMeas['MEAS_CODE']))
# print("len dataMeasSVID['MEAS_CODE'] %d" % len(dataMeasSVID['MEAS_CODE']))
# print dataMeasSVID['MEAS_SVID']
indexSignalType = []
dataMeasSVIDSignalType = []
lliIndicators = []
lliTOWs = []
firstTOW = []
for index, signalType in enumerate(signalTypesSVID):
print('-' * 25)
print("signalType = %s index=%d - name = %s\n" % (signalType, index, mSSN.GNSSSignals[signalType]['name']))
