reserve_neighbor=True)
# --- Peak Grouping
detObj2D = dsp.peak_grouping_along_doppler(detObj2DRaw, det_matrix,
numDopplerBins)
SNRThresholds2 = np.array([[2, 23], [10, 11.5], [35, 16.0]])
peakValThresholds2 = np.array([[4, 275], [1, 400], [500, 0]])
detObj2D = dsp.range_based_pruning(detObj2D, SNRThresholds2,
peakValThresholds2, numRangeBins,
0.5, range_resolution)
azimuthInput = aoa_input[detObj2D['rangeIdx'], :,
detObj2D['dopplerIdx']]
x, y, z = dsp.naive_xyz(azimuthInput.T,
num_tx=numTxAntennas,
num_rx=numRxAntennas,
fft_size=numADCSamples)
xyzVecN = np.zeros((3, x.shape[0]))
xyzVecN[0] = x * range_resolution * detObj2D['rangeIdx']
xyzVecN[1] = y * range_resolution * detObj2D['rangeIdx']
xyzVecN[2] = z * range_resolution * detObj2D['rangeIdx']
Psi, Theta, Ranges, xyzVec = dsp.beamforming_naive_mixed_xyz(
azimuthInput,
detObj2D['rangeIdx'],
range_resolution,
method='Bartlett') # Capon
# (5) 3D-Clustering
# detObj2D must be fully populated and completely accurate right here
numDetObjs = detObj2D.shape[0]
numDopplerBins,
reserve_neighbor=True)
# --- Peak Grouping
detObj2D = dsp.peak_grouping_along_doppler(detObj2DRaw, det_matrix,
numDopplerBins)
SNRThresholds2 = np.array([[2, 23], [10, 11.5], [35, 16.0]])
peakValThresholds2 = np.array([[4, 275], [1, 400], [500, 0]])
detObj2D = dsp.range_based_pruning(detObj2D, SNRThresholds2,
peakValThresholds2, numRangeBins,
0.5, range_resolution)
azimuthInput = aoa_input[detObj2D['rangeIdx'], :,
detObj2D['dopplerIdx']]
x, y, z = dsp.naive_xyz(azimuthInput.T)
xyzVecN = np.zeros((3, x.shape[0]))
xyzVecN[0] = x * range_resolution * detObj2D['rangeIdx']
xyzVecN[1] = y * range_resolution * detObj2D['rangeIdx']
xyzVecN[2] = z * range_resolution * detObj2D['rangeIdx']
Psi, Theta, Ranges, xyzVec = dsp.beamforming_naive_mixed_xyz(
azimuthInput,
detObj2D['rangeIdx'],
range_resolution,
method='Bartlett')
# (5) 3D-Clustering
# detObj2D must be fully populated and completely accurate right here
numDetObjs = detObj2D.shape[0]
dtf = np.dtype({