Improved PSO and Its Application to CS DOA Estimation

The present direction of arrival (DOA) estimation methods based on the compressive sensing (CS) theory is background at present. Shortcoming of greedy pursuit methods is efficiency to solve sparse recovery. A new algorithm based on Particle Swarm Optimization (PSO) algorithm and orthogonal matching pursuit (OMP) algorithm is proposed. It has less computation time, low estimation error and wide application range, which makes full use of the advantages of PSO and OMP algorithm. To improve algorithm performance, the particle updating system of standard PSO algorithm are improved. The results of simulation experiments show that the proposed algorithm is effective.