Separation of sinusoidal and chirp components using Compressive sensing approach

TL;DR

This paper presents a compressive sensing method for separating sinusoidal and chirp components in linear frequency modulated and radar signals, especially under noisy and overlapping conditions, demonstrating its effectiveness through experiments.

Contribution

It introduces a novel application of compressive sensing for separating sinusoidal and chirp signals in challenging noisy and overlapping scenarios.

Findings

Successful separation demonstrated in experiments

Effective with limited measurements due to sparsity

Applicable to radar and communication signals

Abstract

In this paper we deal with the linear frequency modulated signals and radar signals that are affected by disturbance which is the inevitable phenomenon in everyday communications. The considered cases represent the cases when the signals of interest overlap with other signals or with noise. In order to successfully separate these signals we propose the compressive sensing method, which states that the useful signal part can be separated successfully from a small amount of measurements as long as the acquired signal can be presented as sparse in a certain transformation domain. The effectiveness of our approach is proven experimentally through examples.