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作 者:尧泽昆 王超[1,2] 施庆展 张少卿[3] 袁乃昌[1,2] YAO Zekun;WANG Chao;SHI Qingzhan;ZHANG Shaoqing;YUAN Naichang(College of Electronic Science and Technology,National University of Defense Technology,Changsha 410073,China;State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System,National University of Defense Technology,Changsha 410073,China;Shenyang Aircraft Design&Research Institute,Aviation Industry Corporation of China,Shenyang 110035,China)
机构地区:[1]国防科技大学电子科学学院,湖南长沙410073 [2]国防科技大学电子信息系统复杂电磁环境效应国家重点实验室,湖南长沙410073 [3]中国航空工业集团公司沈阳飞机设计研究所,辽宁沈阳110035
出 处:《系统工程与电子技术》2024年第3期824-830,共7页Systems Engineering and Electronics
摘 要:针对分布式干扰机掩护目标突防雷达网背景下的干扰资源分配问题,提出了一种引入随机密钥的改进离散模拟退火遗传算法(improved discrete simulated annealing genetic algorithm,IDSA-GA)对资源分配过程进行优化。基于雷达网融合检测概率构建干扰效果评估函数,利用IDSA-GA对函数寻优求解。IDSA-GA在模拟退火遗传算法(simulated annealing genetic algorithm,SA-GA)的基础上引入随机密钥,完成算法的离散化;并在迭代的过程中增加记忆功能,克服了过早收敛的现象。仿真结果表明,与GA相比,提出的IDSA-GA收敛迅速,寻优能力强,能有效解决干扰资源优化分配问题。An improved discrete simulated annealing genetic algorithm(IDSA-GA)with random keys is proposed to optimize the resource allocation process in the context of distributed jammers covering target penetration radar networks.An interference effect evaluation function based on the fusion detection probability of radar networks is constructed,and IDSA-GA is used to optimize and solve the function.IDSA-GA introduces random keys on the basis of simulated annealing genetic algorithm(SA-GA)to discretize the algorithm.And during the iteration process,memory function is added to overcome the phenomenon of premature convergence.The simulation results show that compared with GA,the proposed IDSA-GA converges quickly and has strong optimization ability,which can effectively solve the problem of optimizing interference resource allocation.
关 键 词:雷达网 协同干扰 资源分配 模拟退火遗传算法 随机密钥
分 类 号:TN97[电子电信—信号与信息处理]
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