In [ ]:
import radarsimpy
radarsimpy.__version__
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'10.1.0'

Micro-Doppler¶



This is an example of using RadarSimPy to simulate micro-Doppler effect.

Setup FMCW radar¶

Transmitter¶

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 [24e9-4000e6, 24e9+4000e6] GHz
Time ($T$) t 300e-6 s
Transmitted power ($P_t$) tx_power 15 dBm
Pulse repetition period ($PRP$) prp 0.0025 s
Number of pulses pulses 1280

Receiver¶

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 2 Msps
Noise figure ($NF$) noise_figure 8 dB
RF gain/loss ($G_{rf}$) rf_gain 20 dB
Load resistor ($R_L$) load_resistor 500 $\Omega$
Baseband voltage gain ($G_{BB}$) baseband_gain 30 dB
In [ ]:
import numpy as np
from radarsimpy import Radar, Transmitter, Receiver

tx_channel = dict(
    location=(0, 0, 0),
)

tx = Transmitter(f=[24e9-4000e6, 24e9+4000e6],
                 t=300e-6,
                 tx_power=25,
                 prp=0.0025,
                 pulses=1280,
                 channels=[tx_channel])

rx_channel = dict(
    location=(0, 0, 0),
)

rx = Receiver(fs=2e6,
              noise_figure=6,
              rf_gain=20,
              load_resistor=500,
              baseband_gain=30,
              channels=[rx_channel])

radar = Radar(transmitter=tx, receiver=rx)
In [ ]:
target_1 = {
    'model': '../models/turbine.stl',
    'location': (5, 0, 0),
    'rotation': (0, 0, 0),
    'rotation_rate': (0, 30, 0),
    'speed': (0, 0, 0)
}

targets = [target_1]
In [ ]:
from radarsimpy.rt import scene
import time

tic = time.time()
data = scene(radar, targets, density=1, level='pulse')
baseband = data['baseband']
toc = time.time()

print('Exec time:', toc-tic, 's')

Range-Doppler processing¶

In [ ]:
from scipy import signal
import radarsimpy.processing as proc

range_window = signal.chebwin(radar.samples_per_pulse, at=60)
doppler_window = signal.chebwin(radar.transmitter.pulses, at=60)
range_doppler = np.fft.fftshift(proc.range_doppler_fft(baseband, rwin=range_window, dwin=doppler_window), axes=1)
In [ ]:
import plotly.graph_objs as go
from IPython.display import Image

temp = np.abs(range_doppler[0, :, :])
temp = 20 * np.log10(temp)

max_range = (3e8 * radar.receiver.fs *
             radar.transmitter.pulse_length /
             radar.transmitter.bandwidth / 2)
unambiguous_speed = 3e8 / radar.transmitter.prp[0] / \
    radar.transmitter.fc_vect[0] / 2

range_axis = np.linspace(
    0, max_range, radar.samples_per_pulse, endpoint=False)

rng_idx = np.where(np.logical_and(range_axis > 4.5, range_axis < 5.5))

doppler_axis = np.linspace(
    -unambiguous_speed/2, unambiguous_speed/2, radar.transmitter.pulses, endpoint=False)

fig = go.Figure()

fig.add_trace(go.Surface(x=range_axis[rng_idx[0]], y=doppler_axis,
                         z=temp[:, rng_idx[0]], colorscale='Rainbow'))

camera = dict(
    up=dict(x=0, y=0, z=1),
    center=dict(x=0, y=0, z=0),
    eye=dict(x=-1, y=1, z=2)
)

fig.update_layout(
    title='Range Doppler',
    height=800,
    scene=dict(
        xaxis=dict(title='Range (m)', range=[4.5, 5.5]),
        yaxis=dict(title='Velocity (m/s)'),
        zaxis=dict(title='Amplitude (dB)'),
        aspectmode='cube',
        camera=camera,
    ),
    margin=dict(l=0, r=0, b=60, t=100),
    legend=dict(orientation='h'),
)

# fig.show()
Image(fig.to_image(format="jpg", scale=2))
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