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"""
plot_acq_grid.py
Reads GNSS-SDR Acquisition dump .mat file using the provided function and
plots acquisition grid of acquisition statistic of PRN sat
Irene Pérez Riega, 2023. iperrie@inta.es
Modifiable in the file:
sampling_freq - Sampling frequency [Hz]
channels - Number of channels to check if they exist
path - Path to folder which contains raw file
fig_path - Path where plots will be save
plot_all_files - Plot all the files in a folder (True/False)
----
file - Fixed part in files names. In our case: acq_dump
sat - Satellite. In our case: 1
channel - Channel. In our case: 1
execution - In our case: 0
signal_type - In our case: 1
----
lite_view - True for light grid representation
File format:
{path}/{file}_ch_{system}_{signal}_ch_{channel}_{execution}_sat_{sat}.mat
-----------------------------------------------------------------------------
GNSS-SDR is a Global Navigation Satellite System software-defined receiver.
This file is part of GNSS-SDR.
Copyright (C) 2022 (see AUTHORS file for a list of contributors)
SPDX-License-Identifier: GPL-3.0-or-later
-----------------------------------------------------------------------------
"""
import os
import sys
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import CubicSpline
import h5py
# ---------- CHANGE HERE:
path = '/home/labnav/Desktop/TEST_IRENE/acquisition/'
fig_path = '/home/labnav/Desktop/TEST_IRENE/PLOTS/Acquisition/'
plot_all_files = False
if not os.path.exists(fig_path):
os.makedirs(fig_path)
if not plot_all_files:
# ---------- CHANGE HERE:
file = 'acq_dump'
sat = 1
channel = 0
execution = 1
signal_type = 1
lite_view = True
# If lite_view -> sets the number of samples per chip in the graphical
# representation
n_samples_per_chip = 3
d_samples_per_code = 25000
signal_types = {
1: ('G', '1C', 1023), # GPS L1
2: ('G', '2S', 10230), # GPS L2M
3: ('G', 'L5', 10230), # GPS L5
4: ('E', '1B', 4092), # Galileo E1B
5: ('E', '5X', 10230), # Galileo E5
6: ('R', '1G', 511), # Glonass 1G
7: ('R', '2G', 511), # Glonass 2G
8: ('C', 'B1', 2048), # Beidou B1
9: ('C', 'B3', 10230), # Beidou B3
10: ('C', '5C', 10230) # Beidou B2a
}
system, signal, n_chips = signal_types.get(signal_type)
# Load data
filename = (f'{path}{file}_ch_{system}_{signal}_ch_{channel}_{execution}'
f'_sat_{sat}.mat')
img_name_root = (f'{fig_path}{file}_ch_{system}_{signal}_ch_{channel}_'
f'{execution}_sat_{sat}')
with h5py.File(filename, 'r') as data:
acq_grid = data['acq_grid'][:]
n_fft, n_dop_bins = acq_grid.shape
d_max, f_max = np.unravel_index(np.argmax(acq_grid), acq_grid.shape)
doppler_step = data['doppler_step'][0]
doppler_max = data['doppler_max'][0]
freq = np.arange(n_dop_bins) * doppler_step - doppler_max
delay = np.arange(n_fft) / n_fft * n_chips
# Plot data
# --- Acquisition grid (3D)
fig = plt.figure()
plt.gcf().canvas.manager.set_window_title(filename)
if not lite_view:
ax = fig.add_subplot(111, projection='3d')
X, Y = np.meshgrid(freq, delay)
ax.plot_surface(X, Y, acq_grid, cmap='viridis')
ax.set_ylim([min(delay), max(delay)])
else:
delay_interp = (np.arange(n_samples_per_chip * n_chips)
/ n_samples_per_chip)
spline = CubicSpline(delay, acq_grid)
grid_interp = spline(delay_interp)
ax = fig.add_subplot(111, projection='3d')
X, Y = np.meshgrid(freq, delay_interp)
ax.plot_surface(X, Y, grid_interp, cmap='inferno')
ax.set_ylim([min(delay_interp), max(delay_interp)])
ax.set_xlabel('Doppler shift (Hz)')
ax.set_xlim([min(freq), max(freq)])
ax.set_ylabel('Code delay (chips)')
ax.set_zlabel('Test Statistics')
plt.tight_layout()
plt.savefig(img_name_root + '_sample_3D.png')
plt.show()
# --- Acquisition grid (2D)
input_power = 100 # Change Test statistics in Doppler wipe-off plot
fig2, axes = plt.subplots(2, 1, figsize=(8, 6))
plt.gcf().canvas.manager.set_window_title(filename)
axes[0].plot(freq, acq_grid[d_max, :])
axes[0].set_xlim([min(freq), max(freq)])
axes[0].set_xlabel('Doppler shift (Hz)')
axes[0].set_ylabel('Test statistics')
axes[0].set_title(f'Fixed code delay to {(d_max - 1) / n_fft * n_chips} '
f'chips')
normalization = (d_samples_per_code**4) * input_power
axes[1].plot(delay, acq_grid[:, f_max] / normalization)
axes[1].set_xlim([min(delay), max(delay)])
axes[1].set_xlabel('Code delay (chips)')
axes[1].set_ylabel('Test statistics')
axes[1].set_title(f'Doppler wipe-off = '
f'{str((f_max-1) * doppler_step - doppler_max)} Hz')
plt.tight_layout()
plt.savefig(img_name_root + '_sample_2D.png')
plt.show()
else:
# ---------- CHANGE HERE:
lite_view = True
# If lite_view -> sets the number of samples per chip in the graphical
# representation
n_samples_per_chip = 3
d_samples_per_code = 25000
filenames = os.listdir(path)
for filename in filenames:
sat = 1
channel = 0
execution = 1
system = filename[12]
signal = filename[14:16]
if system == "G":
if signal == "1C":
n_chips = 1023
elif signal == "2S" or "L5":
n_chips = 10230
else:
print("Incorrect files format. Change the code or the "
"filenames.")
sys.exit()
elif system == "E":
if signal == "1B":
n_chips = 4092
elif signal == "5X":
n_chips = 10230
else:
print("Incorrect files format. Change the code or the "
"filenames.")
sys.exit()
elif system == "R":
if signal == "1G" or "2G":
n_chips = 511
else:
print("Incorrect files format. Change the code or the "
"filenames.")
sys.exit()
elif system == "C":
if signal == "B1":
n_chips = 2048
elif signal == "B3" or "5C":
n_chips = 10230
else:
print("Incorrect files format. Change the code or the "
"filenames.")
sys.exit()
complete_path = path + filename
with h5py.File(complete_path, 'r') as data:
acq_grid = data['acq_grid'][:]
n_fft, n_dop_bins = acq_grid.shape
d_max, f_max = np.unravel_index(np.argmax(acq_grid),
acq_grid.shape)
doppler_step = data['doppler_step'][0]
doppler_max = data['doppler_max'][0]
freq = np.arange(n_dop_bins) * doppler_step - doppler_max
delay = np.arange(n_fft) / n_fft * n_chips
# Plot data
# --- Acquisition grid (3D)
fig = plt.figure()
plt.gcf().canvas.manager.set_window_title(filename)
if not lite_view:
ax = fig.add_subplot(111, projection='3d')
X, Y = np.meshgrid(freq, delay)
ax.plot_surface(X, Y, acq_grid, cmap='viridis')
ax.set_ylim([min(delay), max(delay)])
else:
delay_interp = (np.arange(n_samples_per_chip * n_chips)
/ n_samples_per_chip)
spline = CubicSpline(delay, acq_grid)
grid_interp = spline(delay_interp)
ax = fig.add_subplot(111, projection='3d')
X, Y = np.meshgrid(freq, delay_interp)
ax.plot_surface(X, Y, grid_interp, cmap='inferno')
ax.set_ylim([min(delay_interp), max(delay_interp)])
ax.set_xlabel('Doppler shift (Hz)')
ax.set_xlim([min(freq), max(freq)])
ax.set_ylabel('Code delay (chips)')
ax.set_zlabel('Test Statistics')
plt.savefig(os.path.join(fig_path, filename[:-4]) + '_3D.png')
plt.close()
# --- Acquisition grid (2D)
input_power = 100 # Change Test statistics in Doppler wipe-off plot
fig2, axes = plt.subplots(2, 1, figsize=(8, 6))
plt.gcf().canvas.manager.set_window_title(filename)
axes[0].plot(freq, acq_grid[d_max, :])
axes[0].set_xlim([min(freq), max(freq)])
axes[0].set_xlabel('Doppler shift (Hz)')
axes[0].set_ylabel('Test statistics')
axes[0].set_title(f'Fixed code delay to '
f'{(d_max - 1) / n_fft * n_chips} chips')
normalization = (d_samples_per_code ** 4) * input_power
axes[1].plot(delay, acq_grid[:, f_max] / normalization)
axes[1].set_xlim([min(delay), max(delay)])
axes[1].set_xlabel('Code delay (chips)')
axes[1].set_ylabel('Test statistics')
axes[1].set_title(f'Doppler wipe-off = '
f'{str((f_max - 1) * doppler_step - doppler_max)} '
f'Hz')
plt.tight_layout()
plt.savefig(os.path.join(fig_path, filename[:-4]) + '_2D.png')
# plt.show()
plt.close()
|
