A Partial Relaxation DOA Estimator Based on Orthogonal Matching Pursuit

Abstract

A family of computationally efficient DOA estimators under the partial relaxation framework has recently been proposed. In this framework, the manifold structure of the "interfering" signals is relaxed, and only the manifold structure of one desired signal is retained. This particular type of relaxation results in closed-form estimates for the interference parameters and enhances the estimation performance compared to the conventional spectral-search methods. By adopting the principle of the partial relaxation approach, in this paper, a modification of the Orthogonal Matching Pursuit algorithm is proposed and applied to the Direction-of-Arrival estimation problem. In each iteration of the proposed partial relaxation-based orthogonal matching pursuit (PR-OMP) algorithm, the impact on the receive signal from the previously-estimated directions and the remaining direction with the relaxed steering structure are considered. Simulations show that the proposed PR-OMP algorithm outperforms conventional estimators in the case of low Signal-to-Noise-Ratio or small number of snapshots.