On-Grid DOA Estimation Method Using Orthogonal Matching Pursuit

TL;DR

This paper introduces an on-grid DOA estimation method using Orthogonal Matching Pursuit (OMP), which effectively resolves coherent sources with only one snapshot, outperforming traditional subspace-based algorithms.

Contribution

The paper presents a novel application of OMP for DOA estimation that handles coherent sources directly without covariance matrix modification, using only a single snapshot.

Findings

OMP-based DOA estimation outperforms traditional methods.

The method effectively resolves coherent sources.

It requires only one snapshot for accurate results.

Abstract

Direction of Arrival (DOA) estimation of multiple narrow-band coherent or partially coherent sources is a major challenge in array signal processing. Though many subspace- based algorithms are available in literature, none of them tackle the problem of resolving coherent sources directly, e.g. without modifying the sample data covariance matrix. Compressive Sensing (CS) based sparse recovery algorithms are being applied as a novel technique to this area. In this paper, we introduce Orthogonal Matching Pursuit (OMP) to the DOA estimation problem. We demonstrate how a DOA estimation problem can be modelled for sparse recovery problem and then exploited using OMP to obtain the set of DOAs. Moreover, this algorithm uses only one snapshot to obtain the results. The simulation results demonstrate the validity and advantages of using OMP algorithm over the existing subspace- based algorithms.