火力与指挥控制2016，Vol.41Issue(3)：132-135,139,5.
基于改进自适应遗传算法的阵列优化
Array Optimization Based on a Modified Adaptive Genetic Algorithm
摘要
Abstract
A Modified Adaptive Genetic Algorithm (MAGA)is presented in this paper to optimize the element position of the non-uniform sparse array with the constraints of aperture size,element numbers and minimum element spacing. In the algorithm,real valued coding and the modified fitness function can avoid the appearance of the infeasible solution during mutation and crossover. The new selection operator and improved dual optimal reserved strategy are used in this paper. The classic adaptive probabilities of crossover and mutation are also modified. The simulation results show that the algorithm can suppress premature,increase the probability of obtaining the global optimal solution and get a lower Peak Side-Lobe Level(PSLL).关键词
非均匀稀布阵/改进自适应遗传算法/副瓣电平/阵列优化Key words
non-uniform sparse array/MAGA/PSLL/array optimization分类
电子信息工程引用本文复制引用
黄超,张剑云,朱家兵..基于改进自适应遗传算法的阵列优化[J].火力与指挥控制,2016,41(3):132-135,139,5.基金项目
中国博士后基金（2014M552606）；安徽省自然科学基金资助项目 （）
