A Comparative Study of Sparse Recovery and Compressed Sensing Algorithms with Application to AoA Estimation

Abstract

We investigate the performance of some sparse recovery and compressed sensing algorithms when applied to the Angle-of-Arrival (AoA) estimation problem. In particular, we review three different approaches in compressed sensing, namely Pursuit-type, Thresholding-type, and Bayesian-based algorithms. The compressed sensing algorithms reviewed herein are of vast interest when applied to AoA estimation problems because of their ability to resolve sources with a single snapshot and without prior knowledge of the number of sources. We compare the performance of these algorithms in terms of Mean-Square Error (MSE) through simulations.