def doppler_resolution(self):
_, bw = dsp.range_resolution(
self.cfg['profiles'][0]['adcSamples'],
self.cfg['profiles'][0]['adcSampleRate'] / 1000,
self.cfg['profiles'][0]['freqSlopeConst'] / 1e12)
return dsp.doppler_resolution(
bw,
start_freq_const=self.cfg['profiles'][0]['start_frequency'] / 1e9,
ramp_end_time=self.cfg['profiles'][0]['rampEndTime'] * 1e6,
idle_time_const=self.cfg['profiles'][0]['idle'] * 1e6,
num_loops_per_frame=self.cfg['numChirps'] /
len(self.cfg['chirps']),
num_tx_antennas=self.cfg['numTx'])
# numDopplerBins = numLoopsPerFrame
numDopplerBins = numLoopsPerFrame
numAngleBins = 64
# data processing parameter
numDisplaySamples = 20
range_resolution, bandwidth = dsp.range_resolution(
numADCSamples,
dig_out_sample_rate=configParameters['digOutSampleRate'],
freq_slope_const=configParameters['freqSlopeConst'])
doppler_resolution = dsp.doppler_resolution(
bandwidth,
start_freq_const=configParameters['startFreq'],
ramp_end_time=configParameters['rampEndTime'],
idle_time_const=configParameters['idleTime'],
num_loops_per_frame=configParameters['numLoops'],
num_tx_antennas=numTxAntennas)
print(
f'Range Resolution: {range_resolution}, Bandwidth: {bandwidth}, Doppler Resolution: {doppler_resolution}'
)
ims = []
max_size = 0
# (1) Reading in adc data
if loadData:
adc_data = np.fromfile(adc_data_path, dtype=np.int16)
adc_data = adc_data.reshape(numFrames, -1)
adc_data = np.apply_along_axis(DCA1000.organize,
# QOL settings loadData = True numFrames = 300 numADCSamples = 128 numTxAntennas = 3 numRxAntennas = 4 numLoopsPerFrame = 128 numChirpsPerFrame = numTxAntennas * numLoopsPerFrame numRangeBins = numADCSamples numDopplerBins = numLoopsPerFrame numAngleBins = 64 range_resolution, bandwidth = dsp.range_resolution(numADCSamples) doppler_resolution = dsp.doppler_resolution(bandwidth) plotRangeDopp = False plot2DscatterXY = False plot2DscatterXZ = False plot3Dscatter = True plotCustomPlt = False plotMakeMovie = False makeMovieTitle = "3dscatter" makeMovieDirectory = r"c://Users//Zber//Desktop//mymovie.mp4" visTrigger = plot2DscatterXY + plot2DscatterXZ + plot3Dscatter + plotRangeDopp + plotCustomPlt assert visTrigger < 2, "Can only choose to plot one type of plot at once" singFrameView = False
def generate_spectrum_from_RDC(filename,
numFrames=500,
numADCSamples=128,
numTxAntennas=3,
numRxAntennas=4,
numLoopsPerFrame=128,
numAngleBins=64,
chirpPeriod=0.06,
logGabor=False,
accumulate=True,
save_full=False):
numChirpsPerFrame = numTxAntennas * numLoopsPerFrame
# =============================================================================
# numADCSamples = number of range bins
# numLoopsPerFrame = number of doppler bins
# =============================================================================
range_resolution, bandwidth = dsp.range_resolution(numADCSamples)
doppler_resolution = dsp.doppler_resolution(bandwidth)
if filename[-4:] != '.bin':
filename += '.bin'
adc_data = np.fromfile(filename, dtype=np.int16)
adc_data = adc_data.reshape(numFrames, -1)
adc_data = np.apply_along_axis(DCA1000.organize,
1,
adc_data,
num_chirps=numChirpsPerFrame,
num_rx=numRxAntennas,
num_samples=numADCSamples)
print("Data Loaded!")
dataCube = adc_data
micro_doppler_data = np.zeros((numFrames, numLoopsPerFrame, numADCSamples),
dtype=np.float64)
theta_data = np.zeros((numFrames, numLoopsPerFrame,
numTxAntennas * numRxAntennas, numADCSamples),
dtype=np.complex)
for i, frame in enumerate(dataCube):
# (2) Range Processing
from mmwave.dsp.utils import Window
radar_cube = dsp.range_processing(frame,
window_type_1d=Window.BLACKMAN)
assert radar_cube.shape == (
numChirpsPerFrame, numRxAntennas,
numADCSamples), "[ERROR] Radar cube is not the correct shape!"
# (3) Doppler Processing
det_matrix, theta_data[i] = dsp.doppler_processing(
radar_cube,
num_tx_antennas=3,
clutter_removal_enabled=True,
window_type_2d=Window.HAMMING)
# --- Shifts & Store
det_matrix_vis = np.fft.fftshift(det_matrix, axes=1)
micro_doppler_data[i, :, :] = det_matrix_vis
# Data should now be ready. Needs to be in micro_doppler_data, a 3D-numpy array with shape [numDoppler, numRanges, numFrames]
# LOG GABOR
if logGabor:
if accumulate:
image = micro_doppler_data.sum(axis=1).T
else:
image = micro_doppler_data.T
from LogGabor import LogGabor
import holoviews as hv
lg = LogGabor("default_param.py")
lg.set_size(image)
lg.pe.datapath = 'database/'
image = lg.normalize(image, center=True)
# display input image
# hv.Image(image)
# display log gabor'd image
image = lg.whitening(image) * lg.mask
hv.Image(image)
uDoppler = image
elif accumulate:
uDoppler = micro_doppler_data.sum(axis=1).T
else:
uDoppler = micro_doppler_data.T
if save_full:
return range_resolution, doppler_resolution, uDoppler, theta_data
else:
return range_resolution, doppler_resolution, uDoppler
from etc.config_1 import NUM_CHIRPS, NUM_ADC_SAMPLES, sample_rate, freq_slope, adc_samples, \
start_freq, idle_time, ramp_end_time
# Data specific parameters
# DSP processing parameters
# Data sampling configuration
# Range and Velocity resolution
range_res, band_width = range_resolution(NUM_ADC_SAMPLES, sample_rate,
freq_slope)
# range_res = RANGE_RESOLUTION
print(f'Range Resolution: {range_res} [meters]')
velocity_res = doppler_resolution(band_width, start_freq, ramp_end_time,
idle_time, NUM_CHIRPS, 1)
print(f'Velocity Resolution: {velocity_res} [meters/second]')
# Apply the range resolution factor to the range indices
ranges = np.arange(adc_samples) * range_res
def load_file(file_path, radar_config=None, discard_rx=True):
adc_data = np.fromfile(file_path, dtype=np.uint16)
adc_data = adc_data.reshape(NUM_FRAMES, -1)
all_data = np.apply_along_axis(DCA1000.organize,
1,
adc_data,
num_chirps=NUM_CHIRPS,
num_rx=NUM_RX,
num_samples=NUM_ADC_SAMPLES)
