时空CDMA系统中基于改进PSO的光谱搜索DOA估计

针对传统光谱搜索方法的搜索复杂度和估计精度严格依赖于搜索过程中所用搜索网格数而导致搜索耗时较多的问题,提出了一种基于改进粒子群优化(PSO)的信号到达方向(DOA)估计方法。首先分析了硬约束PSO最小方差无失真响应(MVDR)估计器(HPSO-MVDR);然后针对HPSO-MVDR估计器的不足,提出了一种粒子搜索位置映射技术;最后提出了基于改进PSO MVDR(MPSO-MVDR)估计器。实验结果表明,在角度搜索中结合改进粒子群算法,提出的方法明显降低了搜索复杂度,相比现有光谱搜索方法的估计更加精确。

Spectral searching direction of arrival estimation based on modified particle swarm optimization in time-space CDMA system

To solve the problem of searching complexity and estimating accuracy of the conventional spectral searching methods strictly depend on the number of search grids used during the search, this paper proposes a direction of arrival (DOA) estimation method based on modified particle swarm optimization (PSO). Firstly, the conventional minimum variance distortion less response estimator based on hard-constraint PSO is analyzed. Then a particle search position mapping technique is proposed to overcome the shortage of HPSO-MVSR estimator. Finally, the modified PSO MVDR (MPSO-MVDR) estimator is proposed. The experiments show that the proposed approach can achieve the advantages of reducing search complexity and more accurate estimate over existing conventional spectral searching method.