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基于多目标粒子群优化的同心圆环阵列方向图综合算法
引用本文:王新宽,王桂宝,黄朝军,熊召新. 基于多目标粒子群优化的同心圆环阵列方向图综合算法[J]. 重庆邮电大学学报(自然科学版), 2022, 34(5): 877-885
作者姓名:王新宽  王桂宝  黄朝军  熊召新
作者单位:陕西理工大学 物理与电信工程学院, 陕西 汉中 723001
基金项目:国家自然科学基金(61601272,61772398,61972239);陕西理工大学科学研究计划项目(SLGQD15-12)
摘    要:针对同心圆环阵列(concentric ring antenna array, CRAA)的方向图优化问题,提出了一种新的密度锥削策略(new density tapering strategy, NDT)结合多目标粒子群(multiple objective particle swarm optimization, MOPSO)算法的联合优化方案。基于NDT思想,在阵列口径中心附近始终保持约占总数一半的圆环为满阵填充状态,而对剩余靠近口径外围的圆环,限制它们的填充因子变化范围在两条门限曲线之间;以旁瓣电平和方向性系数为优化目标,通过对单元最小间隔、外围圆环的间距及其填充因子进行优化来寻找可行的Pareto最优解。仿真表明,该方案可用于优化各种口径的CRAA,能在相同或更高方向性系数情况下,降低阵列的旁瓣电平1.25~6.19 dB,达到优化效果。

关 键 词:同心圆环阵列  密度锥削  多目标粒子群优化  旁瓣电平  方向性系数
收稿时间:2021-06-14
修稿时间:2022-08-05

Approach for pattern synthesis of concentric ring antenna arrays based on multiple objective particle swarm optimization
WANG Xinkuan,WANG Guibao,HUANG Chaojun,XIONG Zhaoxin. Approach for pattern synthesis of concentric ring antenna arrays based on multiple objective particle swarm optimization[J]. Journal of Chongqing University of Posts and Telecommunications, 2022, 34(5): 877-885
Authors:WANG Xinkuan  WANG Guibao  HUANG Chaojun  XIONG Zhaoxin
Affiliation:School of Physics and Telecommunication Engineering, Shaanxi University of Technology, Hanzhong 723001, P. R. China
Abstract:Aiming at pattern synthesis of the concentric ring antenna array (CRAA), we propose a joint optimization method, which is based on a new strategy of density tapering (NDT) and combined with multiple objective particle swarm optimization (MOPSO). Based on the idea of NDT, the rings near the center of the array aperture, which account for about half of the total, are kept to be filled. For the remaining rings close to the periphery of the aperture, their filling factors are varied between two threshold curves, both of which are slowly decreased with the increase of ring radius. On this basis, by taking the sidelobe level and directivity coefficient as the optimization targets, the minimum element spacing, the intervals and filling factors of outer rings are optimized by using the algorithm of MOPSO to find the feasible Pareto optima. Some comparative results with the existing algorithms show that this method can be used to optimize CRAA of various aperture sizes, and can reduce the sidelobe level of the array by about 1.25 dB~6.19 dB under the same or higher directivity coefficient.
Keywords:concentric ring array  density tapering  multiple objective particle swarm optimization  sidelobe level  directivity coefficient
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