import radarsimpy
radarsimpy.__version__
'10.0.1'
This is a phase-modulated continuous-wave (PMCW) radar simulation example based on RadarSimPy.
The phase codes in the transmitter channels are defined with phs and t_mod. amp can also be used if there is an amplitude modulation.
In this example, 2 binary phase code sequences are assigned to 2 different transmitter channels.
import numpy as np
code1 = np.array([1, 1, -1, -1, -1, -1, 1, 1, 1, 1, -1, 1, -1, 1, -1, 1,
1, 1, -1, 1, 1, -1, 1, -1, 1, -1, -1, 1, -1, -1, 1, 1,
1, 1, -1, 1, -1, 1, 1, 1, -1, -1, 1, -1, 1, -1, 1, -1,
-1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, -1, 1, 1, -1,
1, -1, -1, 1, -1, 1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1,
1, -1, 1, 1, 1, 1, -1, 1, -1, -1, -1, -1, 1, 1, 1, -1,
1, 1, -1, -1, 1, -1, -1, 1, 1, 1, 1, -1, 1, 1, 1, 1,
-1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, 1, 1, -1, -1, -1,
-1, -1, -1, -1, 1, -1, -1, -1, 1, 1, -1, 1, -1, -1, -1, 1,
1, -1, 1, 1, 1, -1, 1, 1, 1, 1, 1, -1, -1, 1, 1, 1,
1, 1, 1, -1, 1, -1, -1, -1, 1, 1, -1, 1, 1, -1, -1, 1,
-1, -1, 1, -1, -1, 1, 1, 1, -1, -1, -1, 1, -1, -1, 1, -1,
-1, 1, 1, -1, 1, 1, 1, 1, -1, -1, -1, -1, 1, -1, -1, -1,
-1, 1, -1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, 1, 1, -1,
1, 1, 1, -1, 1, -1, 1, 1, 1, -1, -1, 1, 1, 1, -1, -1,
1, -1, -1, 1, -1, 1, 1, 1, 1, 1, -1, -1, -1, 1, 1])
code2 = np.array([1, -1, 1, 1, -1, -1, -1, -1, 1, 1, 1, -1, 1, -1, -1, -1,
-1, 1, -1, -1, 1, -1, 1, -1, -1, -1, -1, 1, -1, -1, 1, -1,
-1, -1, -1, 1, 1, 1, 1, -1, -1, -1, -1, 1, 1, -1, 1, 1,
-1, 1, -1, -1, -1, 1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1,
1, 1, -1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, 1, 1,
-1, 1, -1, 1, 1, 1, -1, 1, -1, -1, 1, -1, -1, -1, -1, -1,
1, 1, 1, 1, -1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1,
1, 1, -1, 1, 1, -1, 1, -1, 1, 1, -1, 1, -1, 1, 1, 1,
-1, -1, 1, 1, -1, -1, -1, -1, 1, -1, -1, -1, -1, 1, 1, -1,
-1, 1, -1, -1, -1, -1, 1, -1, 1, -1, -1, 1, 1, 1, -1, 1,
1, -1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, 1, -1, -1,
1, -1, -1, 1, 1, -1, -1, 1, 1, -1, 1, -1, 1, -1, -1, -1,
-1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1,
-1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, -1, -1, -1, 1, -1,
1, 1, 1, 1, 1, -1, -1, 1, -1, 1, -1, -1, -1, 1, 1, -1,
-1, -1, -1, -1, 1, 1, -1, 1, 1, -1, 1, 1, 1, -1, 1])
phase_code1 = np.zeros(np.shape(code1))
phase_code2 = np.zeros(np.shape(code2))
phase_code1[np.where(code1 == 1)] = 0
phase_code1[np.where(code1 == -1)] = 180
phase_code2[np.where(code2 == 1)] = 0
phase_code2[np.where(code2 == -1)] = 180
t_mod1 = np.arange(0, len(phase_code1))*4e-9
t_mod2 = np.arange(0, len(phase_code2))*4e-9
Plot the phase code sequences
import plotly.graph_objs as go
from IPython.display import Image
fig = go.Figure()
fig.add_trace(go.Scatter(
x=t_mod1,
y=phase_code1,
name='Phase code 1',
))
fig.add_trace(go.Scatter(
x=t_mod2,
y=phase_code2,
name='Phase code 2',
))
fig.update_layout(
title='Phase modulation sequences',
yaxis=dict(title='Phase (deg)'),
xaxis=dict(title='Time (s)'),
)
# fig.show()
# display(SVG(fig.to_image(format='svg', scale=1)))
Image(fig.to_image(format="jpg", scale=2))
Setup the basic transmitter parameters through Transmitter module.
The following table lists the parameters in this example.
| Parameter | Variable in Transmitter |
Value |
|---|---|---|
| Frequency ($f$) | f |
24.125 GHz |
| Time ($T$) | t |
2.1e-6 s |
| Transmitted power ($P_t$) | tx_power |
20 dBm |
| Number of pulses | pulses |
256 |
There are 2 transmitter channels assigned with 2 different phase code sequences. The location of these 2 transmitter channels have 1 m offset in x-axis.
from radarsimpy import Radar, Transmitter, Receiver
tx_channel_1 = dict(
location=(0, 0, 0),
mod_t=t_mod1,
phs=phase_code1,
)
tx_channel_2 = dict(
location=(1, 0, 0),
mod_t=t_mod2,
phs=phase_code2,
)
tx = Transmitter(f=24.125e9,
t=2.1e-6,
tx_power=20,
pulses=256,
channels=[tx_channel_1, tx_channel_2])
Setup the receiver parameters through Receiver module.
The parameters of the receiver are listed in the table below.
| Parameter | Variable in Receiver |
Value |
|---|---|---|
| Sampling rate ($f_s$) | fs |
250 Msps |
| Noise figure ($NF$) | noise_figure |
10 dB |
| RF gain/loss ($G_{rf}$) | rf_gain |
20 dB |
| Load resistor ($R_L$) | load_resistor |
1000 $\Omega$ |
| Baseband voltage gain ($G_{BB}$) | baseband_gain |
30 dB |
rx = Receiver(fs=250e6,
noise_figure=10,
rf_gain=20,
baseband_gain=30,
load_resistor=1000,
channels=[
dict(location=(0, 0, 0))
])
Create the FMCW radar model based on all the parameters defined above.
radar = Radar(transmitter=tx, receiver=rx)
The propertities of targets are defined here. There are 3 targets in this simulation. The locations of the targets are defined through $(x, y, z)$ coordinates in meters, and the speeds of the targets are defined trough $(v_x, v_y, v_z)$ in $m/s$. The propertites of the targets also includes radar cross-section (RCS (dBsm)) and phase (degree).
target_1 = dict(location=(20, 0, 0),
speed=(-200, 0, 0),
rcs=20,
phase=0)
target_2 = dict(location=(70, 0, 0),
speed=(0, 0, 0),
rcs=35,
phase=0)
target_3 = dict(location=(33, 10, 0),
speed=(100, 0, 0),
rcs=20,
phase=0)
targets = [target_1, target_2, target_3]
Use the simulator module to simulate the baseband samples. The user can choose between Python engine simpy or C++ engine simc.
The output baseband data is a 3-D matrix:
$[channels, pulses, ADC~samples]$
# Python engine
from radarsimpy.simulator import simpy
# C++ engine
from radarsimpy.simulator import simc
data = simc(radar, targets, noise=True)
time_matrix = data['timestamp']
data_matrix = data['baseband']
For convenience, the baseband signal for these 2 transmitter channels are separated. So the total size of the baseband data matrix is $2 \times pulses \times samples$.
The baseband of the 2 transmitter channels are simulated separated. For a realistic case, these 2 transmitter channels should tranmit simutaneously. Thus, the baseband of these 2 channels need to be added together
baseband = data_matrix[0, :, :]+data_matrix[1, :, :]
Plot the baseband samples
fig = go.Figure()
fig.add_trace(go.Scatter(
x=time_matrix[0, 0, :],
y=np.real(baseband[0, :]),
name='I',
))
fig.add_trace(go.Scatter(
x=time_matrix[0, 0, :],
y=np.imag(baseband[0, :]),
name='Q',
))
fig.update_layout(
title='I/Q Baseband Signals',
yaxis=dict(title='Amplitude (V)'),
xaxis=dict(title='Time (s)'),
)
# fig.show()
# display(SVG(fig.to_image(format='svg', scale=1)))
Image(fig.to_image(format="jpg", scale=2))