电讯技术2025，Vol.65Issue(2)：275-282,8.DOI:10.20079/j.issn.1001-893x.240314001
基于遗传-群体智能融合算法的干扰决策方法
An Interference Decision-making Method Based on Genetic-Population Intelligent Fusion Algorithm
摘要
Abstract
For the real-time decision-making problem of unmanned aerial vehicle(UAV)swarm cooperative multi-target jamming,a genetic-group intelligent fusion algorithm is proposed.Firstly,the adaptive cooperative jamming benefit evaluation function is constructed according to the working mode and characteristics of the multi-function radar.The characteristics of the NP-hard problem of dynamic jamming decision-making are analyzed,and the multi-factor jamming resource allocation model is established.Then,the genetic-population intelligent fusion algorithm is used to optimize the solution.The proposed algorithm realizes the rapid convergence of the sub-optimal solution in the initial stage of the algorithm through distributed decision-making,and then realizes the global optimization of the algorithm through centralized optimization,and reduces the risk of the algorithm falling into local optimum through the competition and cooperation among individuals in the population.The simulation results show that the fusion algorithm reduces the number of convergence iterations by 42.25%and 15.43%respectively compared with the genetic algorithm and the improved ant colony algorithm.It improves the real-time processing performance by 9.53%compared with the genetic algorithm.The proposed fusion algorithm has better convergence efficiency and real-time processing ability.关键词
无人机集群/协同多目标干扰/干扰资源分配/遗传算法/实时决策/群体智能Key words
UAV swarm/cooperative multi-target jamming/interference resource allocation/genetic algorithm/real-time decision-making/swarm intelligence分类
信息技术与安全科学引用本文复制引用
阎潇,王青平,胡卫东,朱虹宇,王超,施庆展..基于遗传-群体智能融合算法的干扰决策方法[J].电讯技术,2025,65(2):275-282,8.基金项目
国家自然科学基金资助项目(62301570) （62301570）
国防科技创新特区计划(163计划) （163计划）
