Microwave Photonics Computational Signal Algebra Framework for Radar Integrated Sensing and Communication Applications

This work presents a computational signal algebra (CSA) framework for microwave photonics signal processing efforts in radar integrated sensing and communication (RISC) applications, for areas such as parameter estimation, beamforming, and waveform design. The proposed framework presents a set of computational methods, with an associated visualization environment for time-frequency tools such as the short-time Fourier transform (STFT), the cross-ambiguity function (CAF), and the Wigner-Ville distribution (WVD). The discrete ambiguity function (DAF) was implemented as a user defined function (UDF) to be used as a signal correlation analysis and waveform design tool aiming at assisting in research efforts towards efficient use of the electromagnetic spectrum by reducing noise and interference and adhering to spectrum management regulatory standards. Significant computational speedups were obtained for the CAF by introducing novel data sampling algorithmic techniques. Finally, an information flow security framework is proposed utilizing a post-quantum cryptography (PQC) approach in RISC environments.