基于改进型粒子群算法在雷达波束展宽中的应用  

Application of Improved Swarm Algorithm in Radar Beam Broadening

作　　者：董波[1] 陈丁[1] 杨咚咚[1] 盛利利 

机构地区：[1]西安黄河机电有限公司,西安710043

出　　处：《火控雷达技术》2016年第2期18-20,共3页Fire Control Radar Technology

摘　　要：惯性权重是粒子群算法中的关键参数,可以权衡粒子群算法的全局搜索能力及局部搜索能力之间的关系,同时也可以提高算法的收敛性能。针对粒子群算法在处理高维复杂问题时极易陷入局部最优的不足,提出了一种基于适应度累计的周期惯性权重的改进型粒子群优化算法,并通过该算法实现了相控阵雷达天线的波束展宽。Periodic inertia weight is a key parameter of particle swarm algorithm,it can balance between global searching ability and local searching ability; meanwhile it can also improve convergence abilities of algorithm.When particle swarm algorithm is used to process more dimensional and complex problem,it is easy to get into locally optimization. In order to solve this problem,an improved particle swarm algorithm based on adapting periodic inertia weight of fitness cumulative is presented,and beam broadening of phased-array radar antenna is achieved by using the improved particle swarm algorithm.

关 键 词：周期惯性权重 粒子群算法 波束展宽 适应度累计 

分 类 号：TN820[电子电信—信息与通信工程]