Time-Frequency Manifold Representation for Separating and Classifying Frequency Modulation Signals

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.