def test_TrackResultsObj1():
'''
Test for combined channel data iterations.
'''
__testSetup()
tr = TrackingResults('test_output.bin')
assert tr.channelCount() == 2
assert isinstance(tr.getEntries(), list)
assert len(tr.getEntries()) == 2
co = tr.combinedResult()
assert isinstance(co, TrackingResults.MultiChannel)
it = iter(co)
for i in range(500):
tr1, idx1 = it.next()
tr2, idx2 = it.next()
assert tr1.status == 'A'
assert tr2.status == 'B'
assert idx1 == idx2 == i
assert tr1.ms_tracked[i] == i * 2
assert tr2.ms_tracked[i] == i * 2 + 1
try:
it.next()
assert False
except StopIteration:
pass
removeTrackingOutputFiles("test_output.bin")
def test_TrackResultsObj_dump():
'''
Sanity test for combined data output in a textual form.
'''
__testSetup()
tr = TrackingResults('test_output.bin')
tr.dump()
removeTrackingOutputFiles("test_output.bin")
def test_TrackResultsObj_dump():
'''
Sanity test for combined data output in a textual form.
'''
__testSetup()
tr = TrackingResults('test_output.bin')
tr.dump()
removeTrackingOutputFiles("test_output.bin")
def test_TrackResultsObj0():
removeTrackingOutputFiles("test_output.bin")
tr = TrackingResults('test_output.bin')
assert tr.channelCount() == 0
assert isinstance(tr.getEntries(), list)
assert len(tr.getEntries()) == 0
co = tr.combinedResult()
assert isinstance(co, TrackingResults.MultiChannel)
try:
iter(co).next()
assert False
except StopIteration:
pass
def test_TrackResultsObj1():
'''
Test for combined channel data iterations.
'''
__testSetup()
tr = TrackingResults('test_output.bin')
assert tr.channelCount() == 2
assert isinstance(tr.getEntries(), list)
assert len(tr.getEntries()) == 2
co = tr.combinedResult()
assert isinstance(co, TrackingResults.MultiChannel)
it = iter(co)
for i in range(500):
tr1, idx1 = it.next()
tr2, idx2 = it.next()
assert tr1.status == 'A'
assert tr2.status == 'B'
assert idx1 == idx2 == i
assert tr1.ms_tracked[i] == i * 2
assert tr2.ms_tracked[i] == i * 2 + 1
try:
it.next()
assert False
except StopIteration:
pass
removeTrackingOutputFiles("test_output.bin")
def test_TrackResultsObj_single1():
'''
Test for individual channel data iterations.
'''
__testSetup()
tr = TrackingResults('test_output.bin')
assert tr.channelCount() == 2
assert isinstance(tr.getEntries(), list)
assert len(tr.getEntries()) == 2
c0 = tr.channelResult(0)
c1 = tr.channelResult(1)
assert isinstance(c0, TrackingResults.SingleChannel)
assert isinstance(c1, TrackingResults.SingleChannel)
it1 = iter(c0)
it2 = iter(c1)
for i in range(500):
tr1, idx1 = it1.next()
tr2, idx2 = it2.next()
assert tr1.status == 'A'
assert tr2.status == 'B'
assert idx1 == idx2 == i
assert tr1.ms_tracked[i] == i * 2
assert tr2.ms_tracked[i] == i * 2 + 1
try:
it1.next()
assert False
except StopIteration:
pass
try:
it2.next()
assert False
except StopIteration:
pass
removeTrackingOutputFiles("test_output.bin")
def test_TrackResultsObj0():
removeTrackingOutputFiles("test_output.bin")
tr = TrackingResults('test_output.bin')
assert tr.channelCount() == 0
assert isinstance(tr.getEntries(), list)
assert len(tr.getEntries()) == 0
co = tr.combinedResult()
assert isinstance(co, TrackingResults.MultiChannel)
try:
iter(co).next()
assert False
except StopIteration:
pass
def test_TrackResultsObj_single1():
'''
Test for individual channel data iterations.
'''
__testSetup()
tr = TrackingResults('test_output.bin')
assert tr.channelCount() == 2
assert isinstance(tr.getEntries(), list)
assert len(tr.getEntries()) == 2
c0 = tr.channelResult(0)
c1 = tr.channelResult(1)
assert isinstance(c0, TrackingResults.SingleChannel)
assert isinstance(c1, TrackingResults.SingleChannel)
it1 = iter(c0)
it2 = iter(c1)
for i in range(500):
tr1, idx1 = it1.next()
tr2, idx2 = it2.next()
assert tr1.status == 'A'
assert tr2.status == 'B'
assert idx1 == idx2 == i
assert tr1.ms_tracked[i] == i * 2
assert tr2.ms_tracked[i] == i * 2 + 1
try:
it1.next()
assert False
except StopIteration:
pass
try:
it2.next()
assert False
except StopIteration:
pass
removeTrackingOutputFiles("test_output.bin")
def main():
default_logging_config()
parser = argparse.ArgumentParser()
parser.add_argument("-a", "--skip-acquisition",
help="use previously saved acquisition results",
action="store_true")
parser.add_argument("-t", "--skip-tracking",
help="use previously saved tracking results",
action="store_true")
parser.add_argument("-n", "--skip-navigation",
help="use previously saved navigation results",
action="store_true")
populate_peregrine_cmd_line_arguments(parser)
args = parser.parse_args()
if args.no_run:
return 0
if args.file is None:
parser.print_help()
return
if args.profile == 'peregrine' or args.profile == 'custom_rate':
freq_profile = defaults.freq_profile_peregrine
elif args.profile == 'low_rate':
freq_profile = defaults.freq_profile_low_rate
elif args.profile == 'normal_rate':
freq_profile = defaults.freq_profile_normal_rate
elif args.profile == 'high_rate':
freq_profile = defaults.freq_profile_high_rate
else:
raise NotImplementedError()
if args.l1ca_profile:
profile = defaults.l1ca_stage_profiles[args.l1ca_profile]
stage2_coherent_ms = profile[1]['coherent_ms']
stage2_params = profile[1]['loop_filter_params']
else:
stage2_coherent_ms = None
stage2_params = None
if args.pipelining is not None:
tracker_options = {'mode': 'pipelining', 'k': args.pipelining}
else:
tracker_options = None
ms_to_process = int(args.ms_to_process)
skip_samples = 0
if args.skip_samples is not None:
skip_samples = args.skip_samples
if args.skip_ms is not None:
skip_samples = int(args.skip_ms * freq_profile['sampling_freq'] / 1e3)
samples = {gps.L1CA: {'IF': freq_profile['GPS_L1_IF']},
gps.L2C: {'IF': freq_profile['GPS_L2_IF']},
'samples_total': -1,
'sample_index': skip_samples}
# Do acquisition
acq_results_file = args.file + ".acq_results"
if args.skip_acquisition:
logging.info("Skipping acquisition, loading saved acquisition results.")
try:
acq_results = load_acq_results(acq_results_file)
except IOError:
logging.critical("Couldn't open acquisition results file '%s'.",
acq_results_file)
sys.exit(1)
else:
for signal in [gps.L1CA]:
samplesPerCode = int(round(freq_profile['sampling_freq'] /
(gps.l1ca_chip_rate / gps.l1ca_code_length)))
# Get 11ms of acquisition samples for fine frequency estimation
load_samples(samples=samples,
num_samples=11 * samplesPerCode,
filename=args.file,
file_format=args.file_format)
acq = Acquisition(signal,
samples[signal]['samples'],
freq_profile['sampling_freq'],
freq_profile['GPS_L1_IF'],
gps.l1ca_code_period * freq_profile['sampling_freq'],
gps.l1ca_code_length)
# only one signal - L1CA is expected to be acquired at the moment
# TODO: add handling of acquisition results from GLONASS once GLONASS
# acquisition is supported.
acq_results = acq.acquisition(progress_bar_output=args.progress_bar)
print "Acquisition is over!"
try:
save_acq_results(acq_results_file, acq_results)
logging.debug("Saving acquisition results as '%s'" % acq_results_file)
except IOError:
logging.error("Couldn't save acquisition results file '%s'.",
acq_results_file)
# Filter out non-acquired satellites.
acq_results = [ar for ar in acq_results if ar.status == 'A']
if len(acq_results) == 0:
logging.critical("No satellites acquired!")
sys.exit(1)
acq_results.sort(key=attrgetter('snr'), reverse=True)
# Track the acquired satellites
if not args.skip_tracking:
# Remove tracking output files from the previous session.
removeTrackingOutputFiles(args.file)
load_samples(samples=samples,
filename=args.file,
file_format=args.file_format)
if ms_to_process < 0:
ms_to_process = int(
1e3 * samples['samples_total'] / freq_profile['sampling_freq'])
# Create the tracker object, which also create one tracking
# channel per each acquisition result in 'acq_results' list.
tracker = tracking.Tracker(samples=samples,
channels=acq_results,
ms_to_track=ms_to_process,
sampling_freq=freq_profile[
'sampling_freq'], # [Hz]
stage2_coherent_ms=stage2_coherent_ms,
stage2_loop_filter_params=stage2_params,
tracker_options=tracker_options,
output_file=args.file,
progress_bar_output=args.progress_bar,
check_l2c_mask=args.check_l2c_mask)
# The tracking channels are designed to support batch processing.
# In the batch processing mode the data samples are provided in
# batches (chunks) of 'defaults.processing_block_size' bytes size.
# The loop below runs all tracking channels for each batch as it
# reads it from the samples file.
tracker.start()
condition = True
while condition:
# Each tracking channel remembers its own data samples offset within
# 'samples' such that when new batch of data is provided, it
# starts precisely, where it finished at the previous batch
# processing round.
# 'sample_index' is set to the smallest offset within 'samples'
# array across all tracking channels.
sample_index = tracker.run_channels(samples)
if sample_index == samples['sample_index']:
condition = False
else:
samples['sample_index'] = sample_index
load_samples(samples=samples,
filename=args.file,
file_format=args.file_format)
fn_results = tracker.stop()
logging.debug("Saving tracking results as '%s'" % fn_results)
# Do navigation
if not args.skip_navigation:
combinedResultObject = TrackingResults(args.file)
# Dump combined output into a text file
with open(createTrackingDumpOutputFileName(args.file), "wt") as f:
logging.debug("Creating combined tracking file %s", f.name)
combinedResultObject.dump(f)
samplingFreqHz = freq_profile['sampling_freq']
nav_solns = navigation(combinedResultObject, samplingFreqHz)
nav_results = []
for s, t in nav_solns:
nav_results += [(t, s.pos_llh, s.vel_ned)]
if len(nav_results):
print "First nav solution: t=%s lat=%.5f lon=%.5f h=%.1f vel_ned=(%.2f, %.2f, %.2f)" % (
nav_results[0][0],
np.degrees(nav_results[0][1][0]), np.degrees(
nav_results[0][1][1]), nav_results[0][1][2],
nav_results[0][2][0], nav_results[0][2][1], nav_results[0][2][2])
nav_results_file = args.file + ".nav_results"
with open(nav_results_file, 'wb') as f:
cPickle.dump(nav_results, f, protocol=cPickle.HIGHEST_PROTOCOL)
print "and %d more are cPickled in '%s'." % (len(nav_results) - 1, nav_results_file)
else:
print "No navigation results."
def main():
default_logging_config()
parser = argparse.ArgumentParser()
parser.add_argument("-a",
"--skip-acquisition",
help="use previously saved acquisition results",
action="store_true")
parser.add_argument("-t",
"--skip-tracking",
help="use previously saved tracking results",
action="store_true")
parser.add_argument("-n",
"--skip-navigation",
help="use previously saved navigation results",
action="store_true")
populate_peregrine_cmd_line_arguments(parser)
args = parser.parse_args()
if args.no_run:
return 0
if args.file is None:
parser.print_help()
return
if args.profile == 'peregrine' or args.profile == 'custom_rate':
freq_profile = defaults.freq_profile_peregrine
elif args.profile == 'low_rate':
freq_profile = defaults.freq_profile_low_rate
elif args.profile == 'normal_rate':
freq_profile = defaults.freq_profile_normal_rate
elif args.profile == 'high_rate':
freq_profile = defaults.freq_profile_high_rate
else:
raise NotImplementedError()
if args.l1ca_profile:
profile = defaults.l1ca_stage_profiles[args.l1ca_profile]
stage2_coherent_ms = profile[1]['coherent_ms']
stage2_params = profile[1]['loop_filter_params']
else:
stage2_coherent_ms = None
stage2_params = None
if args.pipelining is not None:
tracker_options = {'mode': 'pipelining', 'k': args.pipelining}
else:
tracker_options = None
ms_to_process = int(args.ms_to_process)
skip_samples = 0
if args.skip_samples is not None:
skip_samples = args.skip_samples
if args.skip_ms is not None:
skip_samples = int(args.skip_ms * freq_profile['sampling_freq'] / 1e3)
samples = {
gps.L1CA: {
'IF': freq_profile['GPS_L1_IF']
},
gps.L2C: {
'IF': freq_profile['GPS_L2_IF']
},
'samples_total': -1,
'sample_index': skip_samples
}
# Do acquisition
acq_results_file = args.file + ".acq_results"
if args.skip_acquisition:
logging.info(
"Skipping acquisition, loading saved acquisition results.")
try:
acq_results = load_acq_results(acq_results_file)
except IOError:
logging.critical("Couldn't open acquisition results file '%s'.",
acq_results_file)
sys.exit(1)
else:
for signal in [gps.L1CA]:
samplesPerCode = int(
round(freq_profile['sampling_freq'] /
(gps.l1ca_chip_rate / gps.l1ca_code_length)))
# Get 11ms of acquisition samples for fine frequency estimation
load_samples(samples=samples,
num_samples=11 * samplesPerCode,
filename=args.file,
file_format=args.file_format)
acq = Acquisition(
signal, samples[signal]['samples'],
freq_profile['sampling_freq'], freq_profile['GPS_L1_IF'],
gps.l1ca_code_period * freq_profile['sampling_freq'],
gps.l1ca_code_length)
# only one signal - L1CA is expected to be acquired at the moment
# TODO: add handling of acquisition results from GLONASS once GLONASS
# acquisition is supported.
acq_results = acq.acquisition(
progress_bar_output=args.progress_bar)
print "Acquisition is over!"
try:
save_acq_results(acq_results_file, acq_results)
logging.debug("Saving acquisition results as '%s'" %
acq_results_file)
except IOError:
logging.error("Couldn't save acquisition results file '%s'.",
acq_results_file)
# Filter out non-acquired satellites.
acq_results = [ar for ar in acq_results if ar.status == 'A']
if len(acq_results) == 0:
logging.critical("No satellites acquired!")
sys.exit(1)
acq_results.sort(key=attrgetter('snr'), reverse=True)
# Track the acquired satellites
if not args.skip_tracking:
# Remove tracking output files from the previous session.
removeTrackingOutputFiles(args.file)
load_samples(samples=samples,
filename=args.file,
file_format=args.file_format)
if ms_to_process < 0:
ms_to_process = int(1e3 * samples['samples_total'] /
freq_profile['sampling_freq'])
# Create the tracker object, which also create one tracking
# channel per each acquisition result in 'acq_results' list.
tracker = tracking.Tracker(
samples=samples,
channels=acq_results,
ms_to_track=ms_to_process,
sampling_freq=freq_profile['sampling_freq'], # [Hz]
stage2_coherent_ms=stage2_coherent_ms,
stage2_loop_filter_params=stage2_params,
tracker_options=tracker_options,
output_file=args.file,
progress_bar_output=args.progress_bar,
check_l2c_mask=args.check_l2c_mask)
# The tracking channels are designed to support batch processing.
# In the batch processing mode the data samples are provided in
# batches (chunks) of 'defaults.processing_block_size' bytes size.
# The loop below runs all tracking channels for each batch as it
# reads it from the samples file.
tracker.start()
condition = True
while condition:
# Each tracking channel remembers its own data samples offset within
# 'samples' such that when new batch of data is provided, it
# starts precisely, where it finished at the previous batch
# processing round.
# 'sample_index' is set to the smallest offset within 'samples'
# array across all tracking channels.
sample_index = tracker.run_channels(samples)
if sample_index == samples['sample_index']:
condition = False
else:
samples['sample_index'] = sample_index
load_samples(samples=samples,
filename=args.file,
file_format=args.file_format)
fn_results = tracker.stop()
logging.debug("Saving tracking results as '%s'" % fn_results)
# Do navigation
if not args.skip_navigation:
combinedResultObject = TrackingResults(args.file)
# Dump combined output into a text file
with open(createTrackingDumpOutputFileName(args.file), "wt") as f:
logging.debug("Creating combined tracking file %s", f.name)
combinedResultObject.dump(f)
samplingFreqHz = freq_profile['sampling_freq']
nav_solns = navigation(combinedResultObject, samplingFreqHz)
nav_results = []
for s, t in nav_solns:
nav_results += [(t, s.pos_llh, s.vel_ned)]
if len(nav_results):
print "First nav solution: t=%s lat=%.5f lon=%.5f h=%.1f vel_ned=(%.2f, %.2f, %.2f)" % (
nav_results[0][0], np.degrees(
nav_results[0][1][0]), np.degrees(nav_results[0][1][1]),
nav_results[0][1][2], nav_results[0][2][0],
nav_results[0][2][1], nav_results[0][2][2])
nav_results_file = args.file + ".nav_results"
with open(nav_results_file, 'wb') as f:
cPickle.dump(nav_results, f, protocol=cPickle.HIGHEST_PROTOCOL)
print "and %d more are cPickled in '%s'." % (len(nav_results) - 1,
nav_results_file)
else:
print "No navigation results."