Subspace-based compressive sensing algorithm for raypath separation in a shallow-water waveguide

TL;DR

This paper introduces a subspace-based compressive sensing algorithm designed to effectively separate closely arriving raypaths in shallow-water environments, outperforming existing methods especially under low SNR conditions.

Contribution

The paper proposes a novel subspace-based CS algorithm that incorporates signal subspace statistics for improved raypath separation in multipath underwater acoustics.

Findings

Enables separation of closely arriving raypaths

Performs well in low SNR environments

Outperforms existing algorithms in accuracy

Abstract

Compressive sensing (CS) has been applied to estimate the direction of arrival (DOA) in underwater acoustics. However, the key problem needed to be resolved in a {multipath} propagation environment is to suppress the interferences between the raypaths. Thus, in this paper, {a subspace-based compressive sensing algorithm that formulates the statistic information of the signal subspace in a CS framework is proposed.} The experiment results show that (1) the proposed algorithm enables the separation of raypaths that arrive closely at the {receiver} array and (2) the existing algorithms fail, especially in a low signal-to-noise ratio (SNR) environment.