Frequency Selective Compressed Sensing

TL;DR

This paper introduces a frequency-selective compressed sensing method that enhances signal acquisition by enabling targeted filtering, with a new parameter to evaluate acquisition suitability, demonstrated through numerical experiments.

Contribution

It proposes a novel filtering compressed sensing parameter and demonstrates its effectiveness in frequency-selective signal acquisition.

Findings

The method successfully filters interfered signals in simulations.

The filtering parameter predicts acquisition success.

Numerical experiments validate the approach.

Abstract

In this paper the authors describe the problem of acquisition of interfered signals and formulate a filtering problem. A frequency-selective compressed sensing technique is proposed as a solution to this problem. Signal acquisition is critical in facilitating frequency-selective compressed sensing. The authors propose a filtering compressed sensing parameter, which allows to assess if a given acquisition process makes frequency-selective compressed sensing possible for a given filtering problem. A numerical experiment which shows how the described method works in practice is conducted.