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

Abstract

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

CLC Number:

TN959.73

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.

Figures/Tables 19

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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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Beam space generalized sidelobe canceller algorithm based on particle swarm optimization

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