改进粒子群优化算法自适应波束形成技术  

Adaptive beamforming technique based on a modified particle swarm optimization

作　　者：唐寅洲 赵高泽 TANG Yin-zhou;ZHAO Gao-ze(Kumning Precision Machinery Research Institute,Kunming 650101,China)

机构地区：[1]昆明精密机械研究所,云南昆明650101

出　　处：《舰船科学技术》2018年第9期111-115,共5页Ship Science and Technology

摘　　要：本文研究了利用粒子群优化算法进行自适应方向图控制的综合方法,给出了自适应阵列处理的数学模型以及LCMV自适应波束形成器的数学表达,介绍了粒子群优化算法的基本思想和算法流程。结合粒子群优化算法和自适应方向图控制的相关知识,本文提出一种基于多虚拟干扰源的改进粒子群算法并将其应用于LCMV自适应波束形成器以提升其性能并进行自适应方向图控制。仿真结果表明,该方法可有效改善LCMV自适应波束形成方法在多重干扰情况下零陷生成效果不佳、低快拍下性能较差等缺点,改善输出信干噪比,并在加深零陷和降低旁瓣等方面效果显著。This paper describes the synthesis method of pattern control in adaptive arrays by using particle swarm optimization（PSO） and the conceptual overview and detailed explanation of PSO algorithm. The mathematical model of adaptive array processing and mathematical expression of linearly constraint minimum variance adaptive beamformer are given.Combining particle swarm optimization and adaptive pattern control, a modified PSO algorithm based on multiple artificial interferers is proposed in this paper to enhance the LCMV adaptive beamformer and control the adaptive beam pattern. The design examples show that the proposed algorithm is capable of obtaining higher SINR and steer deep and wide nulls at specific directions effectively. The performance of linearly constraint minimum variance adaptive beamformer is poor when multiple access interference is existing and the size of data snapshots is small and these shortages are improved by using the algorithm proposed in this paper.

关 键 词：粒子群算法 线性约束最小方差 自适应方向图控制 

分 类 号：TB566[交通运输工程—水声工程]