rad-lab 0.0.1

A module for general radar signal processing library

rad-lab

A Python radar module for simulating pulse-Doppler returns and generating range-Doppler maps (RDMs). Designed for radar engineers and students who want to build intuition for how RDMs are formed, how waveforms affect resolution, and how DRFM electronic attack techniques appear in the RDM.

Modules

• rdm — range-Doppler map generation
• pulse_doppler_radar — radar system parameter model
• waveform — uncoded, Barker, random-coded, and LFM pulse generation
• returns — skin return and DRFM jammer return models
• range_equation — radar and one-way link range equations
• uniform_linear_arrays — ULA gain patterns and steering vectors
• monopulse — amplitude monopulse angle estimation
• vbm — velocity bin masking EA slow-time modulation functions
• geometry — range and range-rate from geometry
• noise — complex Gaussian noise generation
• utilities — unit conversions and signal utilities

Installation

Requirements

• Python >= 3.11
• Python packages listed in pyproject.toml
• A few exercises use LaTeX for plot labels — LaTeX must be installed for those to run

Steps

Clone the repository and install with pip:

git clone https://github.com/JohnNehls/radar-signal-processing
pip install radar-signal-processing/

Usage

RDM generator

from rad_lab import rdm, Radar, Target, Return, barker_coded_waveform

radar = Radar(
    fcar=10e9,
    tx_power=1e3,
    tx_gain=10 ** (30 / 10),
    rx_gain=10 ** (30 / 10),
    op_temp=290,
    sample_rate=20e6,
    noise_factor=10 ** (8 / 10),
    total_losses=10 ** (8 / 10),
    prf=200e3,
    dwell_time=2e-3,
)

waveform = barker_coded_waveform(10e6, nchips=13)

return_list = [Return(target=Target(range=0.5e3, range_rate=1.0e3, rcs=1))]

rdm.gen(radar, waveform, return_list)

Other available waveforms: uncoded_waveform, random_coded_waveform, lfm_waveform.

For additional examples including DRFM jammer returns and VBM, see apps/rdms. kitchen_sink.py shows all waveform and return options.

Everything else

For examples of the other module functions, see the exercises.

Testing

• To run the pytests:

python -m pytest tests/ -v

• To run all apps and check for errors:

./apps/run_apps.sh

This script runs all Python files in apps/exercises/, apps/rdms/, and apps/studies/ with the Agg matplotlib backend so no display is required. Files ending in _no_test.py are skipped. The script exits with a non-zero status if any file fails.

Contributing

Contributions are welcome. Please fork the repository and submit a pull request.

License

This project is licensed under the GPL-3.0 License - see LICENSE for details.