Analysis of polynomial FM signals corrupted by heavy-tailed noise

In this paper, we consider the analysis of polynomial FM signals corrupted by additive heavy-tailed noise. Standard timefrequency techniques fail to analyze such signals. For that, we propose here a new technique, named the robust polynomial WignerVille distribution (r-PWVD) to handle this case. We show that this representation outperforms the robust Wigner-Ville distribution (rWVD) and the robust spectrogram in terms of artifacts suppression and high time-frequency resolution for this class of signals. Also, we show that the peak of the r-PWVD is an accurate instantaneous frequency estimator. Examples and Monte-Carlo simulations are presented in order to validate and prove the performance of the proposed algorithm.