指挥控制与仿真2024，Vol.46Issue(5)：45-54,10.DOI:10.3969/j.issn.1673-3819.2024.05.007
基于模糊关联熵的成像侦察星座优化
Optimization of imaging reconnaissance constellation based on relative entropy of fuzzy sets
摘要
Abstract
The optimization of imaging reconnaissance constellation is of great significance for reconnaissance timeliness.At present,evolutionary algorithms based on Pareto are often used in the optimization of reconnaissance constellation.In order to solve the problems of insufficient selection pressure and poor diversity of such algorithms in the optimization of reconnaissance constellation whose objective function dimension is greater than three,the improved particle swarm optimization algorithm based on relative entropy of fuzzy sets(IFREM-PSO)is proposed.The algorithm improves the adaptive inertial weight strategy and enhances the convergence speed and accuracy.The introduction of variation strategy is conducive to jumping out of the local optimal solution.Improve external archive maintenance policy to enhance diversity.Based on the design and opti-mization of regional target-oriented visible light reconnaissance constellation,MOPSO,FREM-PSO and the IFREM-PSO are used to optimize the reconnaissance constellation.The experimental results show that the algorithm based on fuzzy relative en-tropy has a better performance in this problem,and compared with FREM-PSO algorithm,IFREM-PSO algorithm has a sig-nificant improvement in convergence speed,and a better performance in convergence effect and diversity.关键词
高维多目标优化/侦察星座/模糊关联熵/粒子群算法/星座优化Key words
many-objective optimization/reconnaissance constellation/fuzzy relative entropy/particle swarm optimization/constellation optimization分类
军事科技引用本文复制引用
刘亚丽,熊伟,韩驰,熊明晖,于小岚..基于模糊关联熵的成像侦察星座优化[J].指挥控制与仿真,2024,46(5):45-54,10.基金项目
复杂电子系统仿真实验室基金资助项目(6142401003022109) （6142401003022109）
