Add files via upload
This commit is contained in:
NawfalMotii79
GitHub
@@ -0,0 +1,177 @@
|
||||
# %%
|
||||
# Copyright (C) 2024 Analog Devices, Inc.
|
||||
#
|
||||
# All rights reserved.
|
||||
#
|
||||
# Redistribution and use in source and binary forms, with or without modification,
|
||||
# are permitted provided that the following conditions are met:
|
||||
# - Redistributions of source code must retain the above copyright
|
||||
# notice, this list of conditions and the following disclaimer.
|
||||
# - Redistributions in binary form must reproduce the above copyright
|
||||
# notice, this list of conditions and the following disclaimer in
|
||||
# the documentation and/or other materials provided with the
|
||||
# distribution.
|
||||
# - Neither the name of Analog Devices, Inc. nor the names of its
|
||||
# contributors may be used to endorse or promote products derived
|
||||
# from this software without specific prior written permission.
|
||||
# - The use of this software may or may not infringe the patent rights
|
||||
# of one or more patent holders. This license does not release you
|
||||
# from the requirement that you obtain separate licenses from these
|
||||
# patent holders to use this software.
|
||||
# - Use of the software either in source or binary form, must be run
|
||||
# on or directly connected to an Analog Devices Inc. component.
|
||||
#
|
||||
# THIS SOFTWARE IS PROVIDED BY ANALOG DEVICES "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
|
||||
# INCLUDING, BUT NOT LIMITED TO, NON-INFRINGEMENT, MERCHANTABILITY AND FITNESS FOR A
|
||||
# PARTICULAR PURPOSE ARE DISCLAIMED.
|
||||
#
|
||||
# IN NO EVENT SHALL ANALOG DEVICES BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
|
||||
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, INTELLECTUAL PROPERTY
|
||||
# RIGHTS, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
|
||||
# BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
|
||||
# STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF
|
||||
# THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
||||
|
||||
|
||||
# Imports
|
||||
import time
|
||||
import matplotlib
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
plt.close('all')
|
||||
|
||||
|
||||
all_data = np.load(f)
|
||||
|
||||
MTI_filter = '2pulse' # choices are none, 2pulse, or 3pulse
|
||||
max_range = 300
|
||||
min_scale = 4
|
||||
max_scale = 300
|
||||
|
||||
|
||||
# %%
|
||||
""" Calculate and print summary of ramp parameters
|
||||
"""
|
||||
sample_rate = 60e6
|
||||
signal_freq = 30e6
|
||||
output_freq = 10.5e9
|
||||
num_chirps = 256
|
||||
chirp_BW = 25e6
|
||||
ramp_time_s = 0.25e-6
|
||||
frame_length_ms = 0.5e-6 # each chirp is spaced this far apart
|
||||
num_samples = len(all_data[0][0])
|
||||
|
||||
PRI = frame_length_ms / 1e3
|
||||
PRF = 1 / PRI
|
||||
|
||||
# Split into frames
|
||||
N_frame = int(PRI * float(sample_rate))
|
||||
|
||||
# Obtain range-FFT x-axis
|
||||
c = 3e8
|
||||
wavelength = c / output_freq
|
||||
slope = chirp_BW / ramp_time_s
|
||||
freq = np.linspace(-sample_rate / 2, sample_rate / 2, N_frame)
|
||||
dist = (freq - signal_freq) * c / (2 * slope)
|
||||
|
||||
# Resolutions
|
||||
R_res = c / (2 * chirp_BW)
|
||||
v_res = wavelength / (2 * num_chirps * PRI)
|
||||
|
||||
# Doppler spectrum limits
|
||||
max_doppler_freq = PRF / 2
|
||||
max_doppler_vel = max_doppler_freq * wavelength / 2
|
||||
|
||||
print("sample_rate = ", sample_rate/1e6, "MHz, ramp_time = ", int(ramp_time_s*(1e6)), "us, num_chirps = ", num_chirps, ", PRI = ", frame_length_ms, " ms")
|
||||
|
||||
|
||||
# %%
|
||||
# Function to process data
|
||||
def pulse_canceller(radar_data):
|
||||
global num_chirps, num_samples
|
||||
rx_chirps = []
|
||||
rx_chirps = radar_data
|
||||
# create 2 pulse canceller MTI array
|
||||
Chirp2P = np.empty([num_chirps, num_samples])*1j
|
||||
for chirp in range(num_chirps-1):
|
||||
chirpI = rx_chirps[chirp,:]
|
||||
chirpI1 = rx_chirps[chirp+1,:]
|
||||
chirp_correlation = np.correlate(chirpI, chirpI1, 'valid')
|
||||
angle_diff = np.angle(chirp_correlation, deg=False) # returns radians
|
||||
Chirp2P[chirp,:] = (chirpI1 - chirpI * np.exp(-1j*angle_diff[0]))
|
||||
# create 3 pulse canceller MTI array
|
||||
Chirp3P = np.empty([num_chirps, num_samples])*1j
|
||||
for chirp in range(num_chirps-2):
|
||||
chirpI = Chirp2P[chirp,:]
|
||||
chirpI1 = Chirp2P[chirp+1,:]
|
||||
Chirp3P[chirp,:] = chirpI1 - chirpI
|
||||
return Chirp2P, Chirp3P
|
||||
|
||||
def freq_process(data):
|
||||
rx_chirps_fft = np.fft.fftshift(abs(np.fft.fft2(data)))
|
||||
range_doppler_data = np.log10(rx_chirps_fft).T
|
||||
# or this is the longer way to do the fft2 function:
|
||||
# rx_chirps_fft = np.fft.fft(data)
|
||||
# rx_chirps_fft = np.fft.fft(rx_chirps_fft.T).T
|
||||
# rx_chirps_fft = np.fft.fftshift(abs(rx_chirps_fft))
|
||||
range_doppler_data = np.log10(rx_chirps_fft).T
|
||||
num_good = len(range_doppler_data[:,0])
|
||||
center_delete = 0 # delete ground clutter velocity bins around 0 m/s
|
||||
if center_delete != 0:
|
||||
for g in range(center_delete):
|
||||
end_bin = int(num_chirps/2+center_delete/2)
|
||||
range_doppler_data[:,(end_bin-center_delete+g)] = np.zeros(num_good)
|
||||
range_delete = 0 # delete the zero range bins (these are Tx to Rx leakage)
|
||||
if range_delete != 0:
|
||||
for r in range(range_delete):
|
||||
start_bin = int(len(range_doppler_data)/2)
|
||||
range_doppler_data[start_bin+r, :] = np.zeros(num_chirps)
|
||||
range_doppler_data = np.clip(range_doppler_data, min_scale, max_scale) # clip the data to control the max spectrogram scale
|
||||
return range_doppler_data
|
||||
|
||||
# %%
|
||||
# Plot range doppler data, loop through at the end of the data set
|
||||
cmn = ''
|
||||
i = 0
|
||||
raw_data = freq_process(all_data[i])
|
||||
i=int((i+1) % len(all_data))
|
||||
range_doppler_fig, ax = plt.subplots(1, figsize=(7,7))
|
||||
extent = [-max_doppler_vel, max_doppler_vel, dist.min(), dist.max()]
|
||||
cmaps = ['inferno', 'plasma']
|
||||
cmn = cmaps[0]
|
||||
ax.set_xlim([-12, 12])
|
||||
ax.set_ylim([0, max_range])
|
||||
ax.set_yticks(np.arange(0, max_range, 10))
|
||||
ax.set_ylabel('Range [m]')
|
||||
ax.set_title('Range Doppler Spectrum')
|
||||
ax.set_xlabel('Velocity [m/s]')
|
||||
range_doppler = ax.imshow(raw_data, aspect='auto', extent=extent, origin='lower', cmap=matplotlib.colormaps.get_cmap(cmn))
|
||||
|
||||
print("CTRL + c to stop the loop")
|
||||
step_thru_plots = False
|
||||
if step_thru_plots == True:
|
||||
print("Press Enter key to adance to next frame")
|
||||
print("Press 0 then Enter to go back one frame")
|
||||
try:
|
||||
while True:
|
||||
if MTI_filter != 'none':
|
||||
Chirp2P, Chirp3P = pulse_canceller(all_data[i])
|
||||
if MTI_filter == '3pulse':
|
||||
freq_process_data = freq_process(Chirp3P)
|
||||
else:
|
||||
freq_process_data = freq_process(Chirp2P)
|
||||
else:
|
||||
freq_process_data = freq_process(all_data[i])
|
||||
range_doppler.set_data(freq_process_data)
|
||||
plt.show(block=False)
|
||||
plt.pause(0.1)
|
||||
if step_thru_plots == True:
|
||||
val = input()
|
||||
if val == '0':
|
||||
i=int((i-1) % len(all_data))
|
||||
else:
|
||||
i=int((i+1) % len(all_data))
|
||||
else:
|
||||
i=int((i+1) % len(all_data))
|
||||
except KeyboardInterrupt: # press ctrl-c to stop the loop
|
||||
pass
|
||||
Reference in New Issue
Block a user