电波科学学报2024，Vol.39Issue(3)：492-501,10.DOI:10.12265/j.cjors.2023174
基于改进型灰狼优化算法和窗函数加权的稀布矩形平面阵列天线综合
Sparse rectangular planar array antenna synthesis based on improved grey wolf optimizer algorithm and window function weighting
摘要
Abstract
Aiming at the optimization problem of sparsely distributed rectangular planar array antenna under the constraints of array aperture,number of array elements and minimum array element spacing,a synthesis method of sparsely distributed rectangular planar array antenna based on improved grey wolf optimizer(IGWO)algorithm and window function weighting is proposed.Firstly,the grey wolf optimizer(GWO)algorithm is improved by Tent chaotic mapping,nonlinear convergence factor,dominant wolf dynamic confidence strategy and opposition-based learning strategy to increase the population diversity and the ability of the algorithm to jump out of the local optimal.Then,the window function is used to weight the array elements to generate the location distribution matrix,which reduces the time of sparse matrix optimization and improves the optimization efficiency.Finally,the location distribution matrix is used to generate sparse array,and then the IGWO algorithm is used to optimize the thinly distributed under multiple constraints.Simulation experiments are carried out to verify the effectiveness of the proposed method.The experimental results show that the proposed method can effectively improve the performance of the array antenna and reduce the peak sidelobe level.This integrated method is of engineering significance and reference value for solving array distribution problems under multiple constraints.关键词
阵列天线/稀布平面阵列/灰狼优化(GWO)算法/窗函数/峰值旁瓣电平Key words
array antenna/sparse planar arrays/grey wolf optimizer(GWO)algorithm/window function/peak sidelobe level分类
信息技术与安全科学引用本文复制引用
陶奎,王斌,田雪,尹波..基于改进型灰狼优化算法和窗函数加权的稀布矩形平面阵列天线综合[J].电波科学学报,2024,39(3):492-501,10.基金项目
国家自然科学基金(62001074) （62001074）
重庆市研究生科研创新项目(CYS22443) （CYS22443）
