def acquire_data(self, fc, parent_entry, task_id):
tuning_parameters = self.tuning_parameters[fc]
self.configure_usrp(fc, **tuning_parameters)
# Use the radio's actual reported sample rate instead of requested rate
sample_rate = self.usrp.radio.sample_rate
# Build global metadata
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sigmf_md.set_global_field("core:sample_rate", sample_rate)
sigmf_md.set_global_field("core:description", self.description)
sensor_def = capabilities['sensor_definition']
sigmf_md.set_global_field("ntia:sensor_definition", sensor_def)
sigmf_md.set_global_field("ntia:sensor_id", settings.FQDN)
sigmf_md.set_global_field("scos:version", SCOS_TRANSFER_SPEC_VER)
# Acquire data and build per-capture metadata
data = np.array([], dtype=np.complex64)
nsamps = int(sample_rate * tuning_parameters['duration_ms'] * 1e-3)
dt = utils.get_datetime_str_now()
acq = self.usrp.radio.acquire_samples(nsamps).astype(np.complex64)
data = np.append(data, acq)
capture_md = {"core:frequency": fc, "core:datetime": dt}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
annotation_md = {"applied_scale_factor": self.usrp.radio.scale_factor}
sigmf_md.add_annotation(start_index=0, length=nsamps,
metadata=annotation_md)
return data, sigmf_md
def build_sigmf_md(self):
logger.debug("Building SigMF metadata file")
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sigmf_md.set_global_field("core:sample_rate", self.sample_rate)
sigmf_md.set_global_field("core:description", self.description)
try:
sensor_def_obj = SensorDefinition.objects.get()
sensor_def = SensorDefinitionSerializer(sensor_def_obj).data
sigmf_md.set_global_field("scos:sensor_definition", sensor_def)
except SensorDefinition.DoesNotExist:
pass
try:
fqdn = settings.ALLOWED_HOSTS[1]
except IndexError:
fqdn = 'not.set'
sigmf_md.set_global_field("scos:sensor_id", fqdn)
sigmf_md.set_global_field("scos:version", SCOS_TRANSFER_SPEC_VER)
capture_md = {
"core:frequency": self.frequency,
"core:time": utils.get_datetime_str_now()
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
for i, detector in enumerate(M4sDetector):
single_frequency_fft_md = {
"number_of_samples_in_fft": self.fft_size,
"window": "blackman",
"equivalent_noise_bandwidth": self.enbw,
"detector": detector.name + "_power",
"number_of_ffts": self.nffts,
"units": "dBm",
"reference": "not referenced"
}
annotation_md = {
"scos:measurement_type": {
"single_frequency_fft_detection": single_frequency_fft_md,
}
}
sigmf_md.add_annotation(start_index=(i * self.fft_size),
length=self.fft_size,
metadata=annotation_md)
return sigmf_md
def build_sigmf_md(self):
logger.debug("Building SigMF metadata file")
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sigmf_md.set_global_field("core:sample_rate", self.sample_rate)
sigmf_md.set_global_field("core:description", self.description)
sensor_def = capabilities['sensor_definition']
sigmf_md.set_global_field("ntia:sensor_definition", sensor_def)
sigmf_md.set_global_field("ntia:sensor_id", settings.FQDN)
sigmf_md.set_global_field("scos:version", SCOS_TRANSFER_SPEC_VER)
capture_md = {
"core:frequency": self.frequency,
"core:time": utils.get_datetime_str_now()
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
for i, detector in enumerate(M4sDetector):
single_frequency_fft_md = {
"number_of_samples_in_fft": self.fft_size,
"window": "blackman",
"equivalent_noise_bandwidth": self.enbw,
"detector": detector.name + "_power",
"number_of_ffts": self.nffts,
"units": "dBm",
"reference": "not referenced"
}
annotation_md = {
"scos:measurement_type": {
"single_frequency_fft_detection": single_frequency_fft_md,
}
}
sigmf_md.add_annotation(start_index=(i * self.fft_size),
length=self.fft_size,
metadata=annotation_md)
return sigmf_md
def acquire_data(self, parent_entry, task_id):
# Build global metadata
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sigmf_md.set_global_field("core:sample_rate", self.sample_rate)
sigmf_md.set_global_field("core:description", self.description)
try:
sensor_def_obj = SensorDefinition.objects.get()
sensor_def = SensorDefinitionSerializer(sensor_def_obj).data
sigmf_md.set_global_field("scos:sensor_definition", sensor_def)
except SensorDefinition.DoesNotExist:
pass
try:
fqdn = settings.ALLOWED_HOSTS[1]
except IndexError:
fqdn = 'not.set'
sigmf_md.set_global_field("scos:sensor_id", fqdn)
sigmf_md.set_global_field("scos:version", SCOS_TRANSFER_SPEC_VER)
# Acquire data and build per-capture metadata
data = np.array([], dtype=np.complex64)
nsamps = self.nsamples
for idx, fc in enumerate(self.fcs):
self.usrp.radio.tune_frequency(fc)
dt = utils.get_datetime_str_now()
acq = self.usrp.radio.acquire_samples(nsamps).astype(np.complex64)
data = np.append(data, acq)
start_idx = idx * nsamps
capture_md = {"core:frequency": fc, "core:datetime": dt}
sigmf_md.add_capture(start_index=start_idx, metadata=capture_md)
annotation_md = {
"applied_scale_factor": self.usrp.radio.scale_factor
}
sigmf_md.add_annotation(start_index=start_idx, length=nsamps,
metadata=annotation_md)
return data, sigmf_md
def build_sigmf_md(self, task_id, measurement_params, data):
# Build global metadata
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sample_rate = self.sdr.radio.sample_rate
sigmf_md.set_global_field("core:sample_rate", sample_rate)
sensor_def = capabilities["sensor_definition"]
sensor_def["id"] = settings.FQDN
sigmf_md.set_global_field("ntia-sensor:sensor", sensor_def)
action_def = {
"name": self.name,
"description": self.description,
"type": ["TimeDomain"],
}
sigmf_md.set_global_field("ntia-scos:action", action_def)
sigmf_md.set_global_field("ntia-scos:task_id", task_id)
dt = utils.get_datetime_str_now()
num_samples = measurement_params.get_num_samples()
capture_md = {
"core:frequency": self.sdr.radio.frequency,
"core:datetime": dt
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
calibration_annotation_md = self.sdr.radio.create_calibration_annotation(
)
sigmf_md.add_annotation(start_index=0,
length=num_samples,
metadata=calibration_annotation_md)
time_domain_detection_md = {
"ntia-core:annotation_type": "TimeDomainDetection",
"ntia-algorithm:detector": "sample_iq",
"ntia-algorithm:detection_domain": "time",
"ntia-algorithm:number_of_samples": num_samples,
"ntia-algorithm:units": "volts",
"ntia-algorithm:reference": "not referenced",
}
sigmf_md.add_annotation(start_index=0,
length=num_samples,
metadata=time_domain_detection_md)
# Recover the sigan overload flag
sigan_overload = self.sdr.radio.sigan_overload
# Check time domain average power versus calibrated compression
time_domain_avg_power = 10 * np.log10(np.mean(np.abs(data)**2))
time_domain_avg_power += (10 * np.log10(1 / (2 * 50)) + 30
) # Convert log(V^2) to dBm
sensor_overload = (
time_domain_avg_power >
self.sdr.radio.sensor_calibration_data["1db_compression_sensor"])
# Create SensorAnnotation and add gain setting and overload indicators
sensor_annotation_md = {
"ntia-core:annotation_type": "SensorAnnotation",
"ntia-sensor:overload_sensor": sensor_overload,
"ntia-sensor:overload_sigan": sigan_overload,
"ntia-sensor:gain_setting_sigan": measurement_params.gain,
}
location = get_location()
if location:
sensor_annotation_md["core:latitude"] = (location.latitude, )
sensor_annotation_md["core:longitude"] = location.longitude
sigmf_md.add_annotation(start_index=0,
length=num_samples,
metadata=sensor_annotation_md)
return sigmf_md
def build_sigmf_md(
self,
task_id,
measurement_params,
data,
schedule_entry,
recording_id,
start_time,
end_time,
):
frequency = self.sdr.radio.frequency
sample_rate = self.sdr.radio.sample_rate
# Build global metadata
sigmf_md = SigMFFile()
sigmf_md.set_global_info(
GLOBAL_INFO.copy()
) # prevent GLOBAL_INFO from being modified by sigmf
sigmf_md.set_global_field(
"core:datatype", "cf32_le"
) # 2x 32-bit float, Little Endian
sigmf_md.set_global_field("core:sample_rate", sample_rate)
measurement_object = {
"time_start": start_time,
"time_stop": end_time,
"domain": "Time",
"measurement_type": "survey"
if self.is_multirecording
else "single-frequency",
"frequency_tuned_low": frequency,
"frequency_tuned_high": frequency,
}
sigmf_md.set_global_field("ntia-core:measurement", measurement_object)
sensor = capabilities["sensor"]
sensor["id"] = settings.FQDN
get_sensor_location_sigmf(sensor)
sigmf_md.set_global_field("ntia-sensor:sensor", sensor)
from status.views import get_last_calibration_time
sigmf_md.set_global_field(
"ntia-sensor:calibration_datetime", get_last_calibration_time()
)
action_def = {
"name": self.name,
"description": self.description,
"summary": self.description.splitlines()[0],
}
sigmf_md.set_global_field("ntia-scos:action", action_def)
if self.is_multirecording:
sigmf_md.set_global_field("ntia-scos:recording", recording_id)
sigmf_md.set_global_field("ntia-scos:task", task_id)
from schedule.serializers import ScheduleEntrySerializer
serializer = ScheduleEntrySerializer(
schedule_entry, context={"request": schedule_entry.request}
)
schedule_entry_json = serializer.to_sigmf_json()
schedule_entry_json["id"] = schedule_entry.name
sigmf_md.set_global_field("ntia-scos:schedule", schedule_entry_json)
sigmf_md.set_global_field(
"ntia-location:coordinate_system", get_coordinate_system_sigmf()
)
num_samples = measurement_params.get_num_samples()
capture_md = {
"core:frequency": frequency,
"core:datetime": self.sdr.radio.capture_time,
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
calibration_annotation_md = self.sdr.radio.create_calibration_annotation()
sigmf_md.add_annotation(
start_index=0, length=num_samples, metadata=calibration_annotation_md
)
time_domain_detection_md = {
"ntia-core:annotation_type": "TimeDomainDetection",
"ntia-algorithm:detector": "sample_iq",
"ntia-algorithm:number_of_samples": num_samples,
"ntia-algorithm:units": "volts",
"ntia-algorithm:reference": "preselector input",
}
sigmf_md.add_annotation(
start_index=0, length=num_samples, metadata=time_domain_detection_md
)
# Recover the sigan overload flag
sigan_overload = self.sdr.radio.sigan_overload
# Check time domain average power versus calibrated compression
time_domain_avg_power = 10 * np.log10(np.mean(np.abs(data) ** 2))
time_domain_avg_power += (
10 * np.log10(1 / (2 * 50)) + 30
) # Convert log(V^2) to dBm
sensor_overload = False
# explicitly check is not None since 1db compression could be 0
if self.sdr.radio.sensor_calibration_data["1db_compression_sensor"] is not None:
sensor_overload = (
time_domain_avg_power
> self.sdr.radio.sensor_calibration_data["1db_compression_sensor"]
)
# Create SensorAnnotation and add gain setting and overload indicators
sensor_annotation_md = {
"ntia-core:annotation_type": "SensorAnnotation",
"ntia-sensor:overload": sensor_overload or sigan_overload,
"ntia-sensor:gain_setting_sigan": measurement_params.gain,
}
sigmf_md.add_annotation(
start_index=0, length=num_samples, metadata=sensor_annotation_md
)
return sigmf_md
def build_sigmf_md(self, task_id, data, schedule_entry, start_time,
end_time):
logger.debug("Building SigMF metadata file")
# Use the radio's actual reported sample rate instead of requested rate
sample_rate = self.sdr.radio.sample_rate
frequency = self.sdr.radio.frequency
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO.copy(
)) # prevent GLOBAL_INFO from being modified by sigmf
sigmf_md.set_global_field("core:datatype",
"rf32_le") # 32-bit float, Little Endian
sigmf_md.set_global_field("core:sample_rate", sample_rate)
measurement_object = {
"time_start": start_time,
"time_stop": end_time,
"domain": "Frequency",
"measurement_type": "single-frequency",
"frequency_tuned_low": frequency,
"frequency_tuned_high": frequency,
}
sigmf_md.set_global_field("ntia-core:measurement", measurement_object)
sensor = capabilities["sensor"]
sensor["id"] = settings.FQDN
get_sensor_location_sigmf(sensor)
sigmf_md.set_global_field("ntia-sensor:sensor", sensor)
from status.views import get_last_calibration_time
sigmf_md.set_global_field("ntia-sensor:calibration_datetime",
get_last_calibration_time())
sigmf_md.set_global_field("ntia-scos:task", task_id)
action_def = {
"name": self.name,
"description": self.description,
"summary": self.description.splitlines()[0],
}
sigmf_md.set_global_field("ntia-scos:action", action_def)
from schedule.serializers import ScheduleEntrySerializer
serializer = ScheduleEntrySerializer(
schedule_entry, context={"request": schedule_entry.request})
schedule_entry_json = serializer.to_sigmf_json()
schedule_entry_json["id"] = schedule_entry.name
sigmf_md.set_global_field("ntia-scos:schedule", schedule_entry_json)
sigmf_md.set_global_field("ntia-location:coordinate_system",
get_coordinate_system_sigmf())
capture_md = {
"core:frequency": frequency,
"core:datetime": self.sdr.radio.capture_time,
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
frequencies = get_fft_frequencies(self.measurement_params.fft_size,
sample_rate, frequency).tolist()
for i, detector in enumerate(M4sDetector):
frequency_domain_detection_md = {
"ntia-core:annotation_type":
"FrequencyDomainDetection",
"ntia-algorithm:number_of_samples_in_fft":
self.measurement_params.fft_size,
"ntia-algorithm:window":
"flattop",
"ntia-algorithm:equivalent_noise_bandwidth":
self.enbw,
"ntia-algorithm:detector":
"fft_" + detector.name + "_power",
"ntia-algorithm:number_of_ffts":
self.measurement_params.num_ffts,
"ntia-algorithm:units":
"dBm",
"ntia-algorithm:reference":
"preselector input",
"ntia-algorithm:frequency_start":
frequencies[0],
"ntia-algorithm:frequency_stop":
frequencies[-1],
"ntia-algorithm:frequency_step":
frequencies[1] - frequencies[0],
}
sigmf_md.add_annotation(
start_index=(i * self.measurement_params.fft_size),
length=self.measurement_params.fft_size,
metadata=frequency_domain_detection_md,
)
calibration_annotation_md = self.sdr.radio.create_calibration_annotation(
)
sigmf_md.add_annotation(
start_index=0,
length=self.measurement_params.fft_size * len(M4sDetector),
metadata=calibration_annotation_md,
)
# Recover the sigan overload flag
sigan_overload = self.sdr.radio.sigan_overload
# Check time domain average power versus calibrated compression
flattened_data = data.flatten()
time_domain_avg_power = 10 * np.log10(
np.mean(np.abs(flattened_data)**2))
time_domain_avg_power += (10 * np.log10(1 / (2 * 50)) + 30
) # Convert log(V^2) to dBm
sensor_overload = False
# explicitly check is not None since 1db compression could be 0
if self.sdr.radio.sensor_calibration_data[
"1db_compression_sensor"] is not None:
sensor_overload = (
time_domain_avg_power > self.sdr.radio.
sensor_calibration_data["1db_compression_sensor"])
# Create SensorAnnotation and add gain setting and overload indicators
sensor_annotation_md = {
"ntia-core:annotation_type": "SensorAnnotation",
"ntia-sensor:overload": sensor_overload or sigan_overload,
"ntia-sensor:gain_setting_sigan": self.measurement_params.gain,
}
sigmf_md.add_annotation(
start_index=0,
length=self.measurement_params.fft_size * len(M4sDetector),
metadata=sensor_annotation_md,
)
return sigmf_md
def build_sigmf_md(self, task_id, data):
logger.debug("Building SigMF metadata file")
# Use the radio's actual reported sample rate instead of requested rate
sample_rate = self.sdr.radio.sample_rate
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sigmf_md.set_global_field("core:sample_rate", sample_rate)
sensor_def = capabilities["sensor_definition"]
sensor_def["id"] = settings.FQDN
sigmf_md.set_global_field("ntia-sensor:sensor", sensor_def)
action_def = {
"name": self.name,
"description": self.description,
"type": ["FrequencyDomain"],
}
sigmf_md.set_global_field("ntia-scos:action", action_def)
sigmf_md.set_global_field("ntia-scos:task_id", task_id)
capture_md = {
"core:frequency": self.sdr.radio.frequency,
"core:datetime": utils.get_datetime_str_now(),
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
for i, detector in enumerate(M4sDetector):
frequency_domain_detection_md = {
"ntia-core:annotation_type":
"FrequencyDomainDetection",
"ntia-algorithm:number_of_samples_in_fft":
self.measurement_params.fft_size,
"ntia-algorithm:window":
"flattop",
"ntia-algorithm:equivalent_noise_bandwidth":
self.enbw,
"ntia-algorithm:detector":
detector.name + "_power",
"ntia-algorithm:number_of_ffts":
self.measurement_params.num_ffts,
"ntia-algorithm:units":
"dBm",
"ntia-algorithm:reference":
"not referenced",
"nita-algorithm:detection_domain":
"frequency",
}
sigmf_md.add_annotation(
start_index=(i * self.measurement_params.fft_size),
length=self.measurement_params.fft_size,
metadata=frequency_domain_detection_md,
)
calibration_annotation_md = self.sdr.radio.create_calibration_annotation(
)
sigmf_md.add_annotation(
start_index=0,
length=self.measurement_params.fft_size * len(M4sDetector),
metadata=calibration_annotation_md,
)
# Recover the sigan overload flag
sigan_overload = self.sdr.radio.sigan_overload
# Check time domain average power versus calibrated compression
flattened_data = data.flatten()
time_domain_avg_power = 10 * np.log10(
np.mean(np.abs(flattened_data)**2))
time_domain_avg_power += (10 * np.log10(1 / (2 * 50)) + 30
) # Convert log(V^2) to dBm
sensor_overload = (
time_domain_avg_power >
self.sdr.radio.sensor_calibration_data["1db_compression_sensor"])
# Create SensorAnnotation and add gain setting and overload indicators
sensor_annotation_md = {
"ntia-core:annotation_type": "SensorAnnotation",
"ntia-sensor:overload_sensor": sensor_overload,
"ntia-sensor:overload_sigan": sigan_overload,
"ntia-sensor:gain_setting_sigan": self.measurement_params.gain,
}
location = get_location()
if location:
sensor_annotation_md["core:latitude"] = (location.latitude, )
sensor_annotation_md["core:longitude"] = location.longitude
sigmf_md.add_annotation(
start_index=0,
length=self.measurement_params.fft_size * len(M4sDetector),
metadata=sensor_annotation_md,
)
return sigmf_md
