改进粒子群算法在 DOA 估计中的应用

摘要

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 algo-rithm, which makes full use of the advantages of PSO algorithm and ML method. In order to improve the estimated perfor-mance, the self-adapting inertia, maximum speed and search system of standard PSO algorithm are improved. Simulation results verify that the improved algorithm is effective.%　　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。