minimal raytracing code example for MIMO FMCW radar
Project description
mmWrt
minimal raytracing for MIMO FMCW radar systems.
Intended usage:
- educational
Release Notes and Roadmap
Released
v0.0.3: first release
* point targets only
* 1D compute of baseband if signal for scene
* 1D FFT, CFAR, peak grouping and target position error compute
* single reflections
v0.0.4:
* adding frequency estimator
* added speed processing
* added support for radar equation (RCS, distance, ...)
* antenna gains in azimumth, elevation and freq
NEXT ()
* 2D (AoA)
* 2D FFT: range+velocity, range+AoA
* 2D peak grouping (by velocity sign)
* 3D position error compute
* 3D targets (at least spheres)
* medium attenuation
* 3D point clouds (i.e. over multiple CTI)
* multiple single reflections
Not planned yet but considered:
- reads and loads .bin
- record BB signals in .bin
- 3D targets and scene rendering with imaging side by side radar
- Swerling's scattering
Example Code
Check on Google Colab the code:
Release process
- run pyroma (should be 10/10)
pyroma .
- run flake8 runs with darglint settings for docstrings to numpy standard set in the .flake8 file should yield 0 warnings or errors
flake8
- run pytest should yield 100% pass
pytest
- run coverage
coverage run -m pytest
- run coverage report (should be 100%)
coverage report
- run tox
7.run sphinx-api
updates the *.rst in docs/ folder
sphinx-apidoc -f -o docs mmWrt
- run sphinx-build (updates the read_the_docs folder)
sphinx-build -b html docs build/html
- release to pypi-test
python setup.py bdist_wheel
twine upload -r testpypi dist*
-
update on read_the_docs
-
check on Google Colab (Google Colab requires py3.8 as off 2023-Jan-15)
-
release on pypi
twine upload -r pypi dist*
Project details
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