Memetic particle swarm optimization scheme for direction-of-arrival estimation in multipath environment

Abstract

In a multipath environment, signals generally reach the receiving antenna through two or more paths, causing the existing direction-of-arrival (DOA) estimation methods to be biased. Various particle swarm optimization (PSO) algorithms may provide premature convergence without determining the global optimum. However, the multipath effect is reduced by projecting the received signal onto an appropriate beam space. In this paper, a new memetic PSO (MPSO) scheme is proposed for estimating the DOA in a multipath environment. This scheme addresses the multipath effect by applying local search techniques to PSO, resulting in highly efficient optimization and a reduced multipath effect. The scheme is as follows: First, PSO and the minimum variance distortionless response (MVDR) method are used to estimate the DOA of signals. Second, the individual best position of the swarm and the beam space MVDR (BMVDR) method are used to construct an objective function. Furthermore, the first-order Taylor expansion of the objective function and local search techniques are used to enhance the search accuracy and reduce the search complexity. Two numerical examples are presented to illustrate the design procedure and demonstrate the high performance of the proposed method.