相控阵天线波束形成联合优化算法

doi:10.7523/j.ucas.2022.022

摘要/Abstract

摘要： 针对复杂波束形成时算法收敛速度慢，容易陷入局部最优的问题，提出一种新的联合优化算法。算法立足于天线方向图与阵元电流的傅里叶变换关系，对于目标波束方向图，利用傅里叶逆变换，得到阵列天线各单元的加权值，然后将得到的幅度和相位值作为遗传算法的初始值，在仅相位加权的约束下，最终生成带宽零陷的波束方向图。为防止遗传算法陷入局部最优，将混沌映射的思想引入：用混沌映射来生成初始种群，同时在变异过程中引入混沌扰动，借助Sinusoidal混沌映射的遍历性和随机性在增加初始种群多样性的同时增强算法跳出局部最优的能力。仿真结果显示本文算法能够生成带宽零陷的复杂波束方向图，且不易陷入局部最优值。

关键词: 遗传算法, 波束形成, 唯相加权, sinusoidal混沌映射, 快速傅里叶变换

Abstract: A new combined algorithm is proposed in this paper to solve the problem that the algorithm convergence speed is slow and easy to fall into local convergence in complex beamforming. This algorithm is based on the Fourier transform relationship between the antenna pattern and the current of the array element. For the target beam pattern, the inverse Fourier transform is used to obtain amplitude and phase values of each element in the array antenna. The acquired values as the initial values are input into the genetic algorithm (GA). A complex beam pattern with wide null is finally designed by controlling only the phase. In order to prevent GA from falling into local optimum, chaos map is introduced. The initial population and mutation operation of GA are combined with chaos. With the help of ergodicity and randomness of sinusoidal chaos, the diversity of population and the ability of the algorithm to jump out of the local optimum are enhanced. Synthesis results show that the proposed algorithm can generate complex beam patterns with wide null, and it is not easy to fall into local optimal values.

Key words: genetic algorithm, beamforming, phase-only distribution, sinusoidal chaos map, FFT

中图分类号:

赵明浩, 周以国. 相控阵天线波束形成联合优化算法[J]. 中国科学院大学学报, 2023, 40(6): 771-777.

ZHAO Minghao, ZHOU Yiguo. Combined algorithm for phased array antenna beamforming[J]. Journal of University of Chinese Academy of Sciences, 2023, 40(6): 771-777.

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