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A toolkit for simulating stochastic and/or deterministic radio frequency aggregate spectrum (in both in-phase/quadrature and image formats) for testing sensing algorithms (e.g. detection, parameter estimation, classification).

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vtnsi/pywaspgen

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Welcome to the PyWASPGEN Python Package!

PyWASPGEN (Python Wideband Aggregate SPectrum GENerator) is intended as a native python dataset generation tool for creating synthetic aggregate radio frequency captures for initial testing and evaluation of spectrum sensing algorithms. The data produced by this tool is particularly useful for testing signal detection algorithms (i.e. where in time and frequency signals exist in the capture) as well as signal classification algorithms (i.e. what is the signaling format of the detected signal).

Installation

Use the package manager pip to install PyWASPGEN from the root directory of the repository.

pip install .

For Developers

If you're interested in contributing to the development of PyWASPGEN, you'll need to install pre-commit.

pip install pre-commit
pre-commit install

Usage

Generating synthetic radio frequency captures using PyWASPGEN can either be done directly through user-specified signal generation parameters or pseudorandomly through user-specified signal generation parameter ranges.

Direct Capture Generation (see example script below for detailed comments)

python examples/direct_generation.py

Pseudorandom Capture Generation (see example script below for detailed comments)

python examples/random_generation.py

Acknowledgements

PyWASPGEN is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract HQ003419D0003. The Systems Engineering Research Center (SERC) is a federally funded University Affiliated Research Center managed by Stevens Institute of Technology. Any views, opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Department of Defense nor ASD(R&E).

Contributors

Name Role Title Email
William 'Chris' Headley Developer Associate Director, Spectrum Dominance Division, Virginia Tech National Security Institute cheadley@vt.edu
Caleb McIrvin Developer PhD Student, Spectrum Dominance Division, Virginia Tech National Security Institute calebmcirvin111@vt.edu
Michael 'Alex' Kyer Developer Software Engineer, Intelligent Systems Division, Virginia Tech National Security Institute makyer19@vt.edu

License

MIT

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A toolkit for simulating stochastic and/or deterministic radio frequency aggregate spectrum (in both in-phase/quadrature and image formats) for testing sensing algorithms (e.g. detection, parameter estimation, classification).

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