An effective technique for the IF estimation of FM signals in heavy-tailed noise

In this paper, we consider the analysis of frequency modulated (FM) signals corrupted by heavy-tailed additive noise. Here, we use time-frequency analysis for such signals. However, for a good performance, we need a pre-processing of the noisy signal. This pre-processing stage is based on compressing the input signal in order to increase the output signal-to-noise ratio. This result is demonstrated theoretically and by simulations. Also, we show that the proposed technique is very effective in estimating the instantaneous frequency (IF) of the noisy signal.

[1]  Braham Barkat.  Instantaneous frequency estimation of nonlinear frequency-modulated signals in the presence of multiplicative and additive noise , 2001, IEEE Trans. Signal Process..

[2]  Braham Barkat,et al.  Instantaneous frequency estimation of polynomial FM signals using the peak of the PWVD: statistical performance in the presence of additive gaussian noise , 1999, IEEE Trans. Signal Process..

[3]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[4]  I. Miller.  Probability, Random Variables, and Stochastic Processes , 1966 .

[5]  Jerry D. Gibson,et al.  Digital coding of waveforms: Principles and applications to speech and video , 1985, Proceedings of the IEEE.

[6]  Boualem Boashash,et al.  Time-Frequency Signal Analysis: Methods and Applications. , 1993 .

[7]  LJubisa Stankovic,et al.  Instantaneous frequency estimation using the Wigner distribution with varying and data-driven window length , 1998, IEEE Trans. Signal Process..

[8]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[9]  N. Jayant,et al.  Digital Coding of Waveforms: Principles and Applications to Speech and Video , 1990 .

[10]  S. Kassam.  Signal Detection in Non-Gaussian Noise , 1987 .

[11]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[12]  F. Hlawatsch,et al.  Linear and quadratic time-frequency signal representations , 1992, IEEE Signal Processing Magazine.

[13]  Vladimir Katkovnik.  Robust M-periodogram , 1998, IEEE Trans. Signal Process..

[14]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .