基于粒子群优化的波束空间广义旁瓣相消算法

doi:10.12305/j.issn.1001-506X.2022.10.06

摘要/Abstract

摘要：

针对广义旁瓣相消(generalized sidelobe canceller, GSC)算法运算量大, 在波束形成中存在旁瓣较高、稳健性差的问题, 提出一种基于粒子群优化(particle swarm optimization, PSO)的波束空间GSC算法。首先, 建立一种优化自适应转换矩阵将信号处理过程由阵元空间转换到波束空间, 通过减小自由度来降低算法的运算量。其次, 构建最小均方误差适应度函数, 在波束空间中利用压缩因子PSO算法充分利用接收数据的相关性, 缩减与期望信号误差并降低波束旁瓣。所提算法在降低算法运算量的同时, 解决了波束旁瓣过高的问题, 并在低快拍、强干扰条件下具有较好波束形成能力, 算法稳健性好。

关键词: 波束形成, 自适应转换矩阵, 粒子群优化, 压缩因子, 稳健性

Abstract:

In view of the large amount of computation of the generalized sidelobe canceller (GSC) algorithm, there are problems of high sidelobe and poor robustness in beamforming. A method based on particle swarm optimization (PSO) is proposed. Firstly, an optimized adaptive conversion matrix is established to transform the signal processing process from array element space to beam space, and the computational complexity of the algorithm is reduced by reducing the degree of freedom. Secondly, the minimum mean square error fitness function is constructed, and the compression factor PSO algorithm is used in the beam space. The correlation of the received data is used to reduce the error with the desired signal and reduce the beam sidelobe. The proposed algorithm not only reduces the amount of calculation, but also solves the problem of too high beam sidelobe. It has good beamforming ability and good robustness under the conditions of low snapshot and strong interference.

Key words: beamforming, adaptive transformation matrix, particle swarm optimization (PSO), compression factor, robustness

中图分类号:

TN959.73

李浩洋, 向建军, 彭芳, 王帅, 李志军. 基于粒子群优化的波束空间广义旁瓣相消算法[J]. 系统工程与电子技术, 2022, 44(10): 3037-3045.

Haoyang LI, Jianjun XIANG, Fang PENG, Shuai WANG, Zhijun LI. Beam space generalized sidelobe canceller algorithm based on particle swarm optimization[J]. Systems Engineering and Electronics, 2022, 44(10): 3037-3045.

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GSC算法	PSO-GSC算法	BS-GSC算法	本文算法
O(LN²+N³+KN²)	O(LN²+^MQLN+N³+KN²)	O(L(NN_bs+N_bs²)+N_bs³+KN_bs²)	O(L(NN_bs+N_bs²)+MQLN_bs+N_bs³+KN_bs²)

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