改进粒子群算法在DOA估计中的应用

针对均匀线性阵列的相干信号波达方向（DOA）估计问题，提出了一种结合粒子群优化（PSO）算法和最大似然函数的解相干算法。算法充分利用了PSO算法解决优化问题的优势和最大似然测向的优点，对独立信号、相干信号或二者的混合信号的DOA都能进行有效的估计。为了提高估计性能，对标准PSO算法的惯性权重、最大速度和搜索机制进行了改进。仿真结果证明了改进算法的有效性。

Improved PSO and its application to DOA estimation

A new decorrelation algorithm based on Particle Swarm Optimization（PSO） algorithm and Maximum Likelihood（ML） function is proposed for Direction-Of-Arrival（DOA） estimation of coherent signals on Uniform Linear Array（ULA）. The DOA of independent signals, coherent signals or both of the mixed signals can be effectively estimated by proposed algorithm, which makes full use of the advantages of PSO algorithm and ML method. In order to improve the estimated performance, the self-adapting inertia, maximum speed and search system of standard PSO algorithm are improved. Simulation results verify that the improved algorithm is effective.