Instantaneous frequency estimation in compressive sensing scenario

TL;DR

This paper presents a method for estimating the instantaneous frequency of nonstationary signals using compressive sensing to reconstruct missing parts of the time-frequency representation, specifically the S-method, and verifies the approach through experiments.

Contribution

It introduces a novel approach combining compressive sensing with the S-method for instantaneous frequency estimation from incomplete time-frequency data.

Findings

Accurate frequency estimation from incomplete time-frequency representations.

Effective reconstruction of missing coefficients using compressive sensing algorithms.

Experimental validation confirms the method's reliability.

Abstract

In this paper, the instantaneous frequency estimation of nonstationary signals is considered. The instantaneous frequency is estimated from the timefrequency representation where certain percent of the coefficients is missing. The time-frequency representation is considered as an image, whose missing pixels are reconstructed by using compressive sensing recovery algorithms. As a time-frequency representation, the S-method is considered. The Compressive Sensing as a intensively growing novel approach for signal acquisition, ensures accurate signal reconstruction from relatively small percent of available information about the signal. The theory is verified by experimental results.