Maximum Likelihood DOA Estimation Using Particle Swarm Optimization Algorithm
Zeng Jiankui, He Zishu, Liu benyong · 2006
Direction-of-arrival (DOA) estimation is an important problem. Many algorithms have been proposed. The maximum likelihood (ML) is one of the good solutions. This paper presents an application of particle swarm optimization (PSO) developed for obtaining the global optimal solution of ML DOA estimation. It overcomes the local optima problem existing in some ML DOA estimation algorithms and improves the estimation accuracy. The computation complexity is modest