基于动态搜索策略离散粒子群算法的稀疏阵列约束优化  

Constrained Optimization for Thinned Array Based on Discrete Particle Swarm Optimization with Dynamic Search Strategy

作　　者：曾浩[1] 蔡万翰 任志刚[2] 陈毅乔[2] ZENG Hao;CAI Wan-han;REN Zhi-gang;CHEN Yi-qiao(School of Microelectronics and Communication Engineering,Chongqing University,Chongqing 400044,China;Southwest China Institute of Electronic Technology,Chengdu,Sichuan 610036,China)

机构地区：[1]重庆大学微电子与通信工程学院,重庆400044 [2]西南电子技术研究所,四川成都610036

出　　处：《电子学报》2023年第4期783-791,共9页Acta Electronica Sinica

基　　金：“十四五”国防预研基金(No.629010204)。

摘　　要：针对目前稀疏阵列优化算法搜索策略单一和适用范围受限问题,对离散粒子群(Discrete Particle Swarm Optimization,DPSO)算法进行改进,提出了一种基于多种融合的综合粒子学习策略的算法,用其设计具有多个约束条件的稀疏平面阵列.该方法在粒子速度更新时使用基于小生境的分散解集合替换群体最优解,以形成高多样性种群.为了增强后期局部收敛性,在适时启动局部变异策略,利用变异概率自适应地调整粒子位置,并通过两个观测参数监控其运动状态.经典函数测试和平面稀疏阵列数值仿真结果证明了算法的有效性和鲁棒性.相同仿真条件下,相比于现有三种算法,该算法峰值旁瓣电平(Peak Side-Lobe Level,PSLL)分别降低了8.45%,6.77%和8.27%.A novel optimization algorithm for large array thinning based on discrete particle swarm optimization(DP⁃SO)with dynamic search strategy is proposed to solve the problem of single search focus and limited application scope of ex⁃isting algorithms.The proposed algorithm named dynamic search strategy DPSO(DSSDPSO)utilizes a global learning strate⁃gy to improve the diversity of swarm at the early stage of optimization.A niche-based dispersive solution set is used to replace the best position found by the swarm during particle velocity updating.Then a local mutation strategy is enabled in the later stage of optimization.The particle position is adaptively adjusted by the mutation probability,and its motion state is monitored by two observation parameters.Several representative examples of large planar arrays thinning are provided to demonstrate the effectiveness and robustness of the DSSDPSO algorithm.Under the same simulation conditions,this algorithm reduces the peak side-lobe level by 8.45%,6.77%and 8.27%respectively compared with the other three existing similar algorithms.

关 键 词：稀疏阵列 离散粒子群算法 搜索策略 多样性 模式搜索 峰值旁瓣电平 

分 类 号：TN820.1[电子电信—信息与通信工程] TN821.8