Time-frequency manifold representation for separating and classifying frequency modulation signals

Bing C. Li

doi:10.1117/12.2586084

12 April 2021 Time-frequency manifold representation for separating and classifying frequency modulation signals

Bing C. Li

Proceedings Volume 11742, Radar Sensor Technology XXV; 1174203 (2021) https://doi.org/10.1117/12.2586084
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

In high density communication and radar environments, radio frequency (RF) signal processing for receivers faces significant challenges. Receivers may receive the overlapped or pulse-on-pulse (POP) RF signals transmitted by cochannel and co-site RF emitters. Detecting, separating, and classifying these POP signals are valuable, but difficult due to the overlapping in time and frequency. In this paper, we propose a time-frequency manifold representation to solve these challenging problems. Using time frequency analysis, we show that a frequency modulation RF (FMRF) signal can be represented as a one dimensional manifold embedded in a two dimensional time frequency space. Using graph theory, we propose a path finding approach to extract this time frequency manifold. With both theoretical analysis and experiments, we show that the proposed approach can extract both simple single and complicated pulse-on-pulse FMRF signals

Conference Presentation

Citation Download Citation

Bing C. Li "Time-frequency manifold representation for separating and classifying frequency modulation signals", Proc. SPIE 11742, Radar Sensor Technology XXV, 1174203 (12 April 2021); https://doi.org/10.1117/12.2586084

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