摘要
雷达网布站优化是电子对抗仿真的重要组成部分,雷达网布站是否合理直接影响雷达网作战效能。而常规优化算法相对复杂,易陷于局部最优解。针对这一问题,提出适用于解决雷达网布站优化问题的改进粒子群优化算法,并且将所提出的算法与遗传算法进行了比较。仿真结果表明,与遗传算法相比,在相同的条件下,改进粒子群优化算法具有精度较高且不易陷入局部最优解的优点,较好地解决了静态条件下雷达网布站优化问题。
Deployment optimization of radar net is one of the most important functions of EW simulation system. The result of deployment optimization has great influence on the radar net effect. At present, the existing optimization algorithm can not meet the demand of simulation for its complexity and long computing time. Therefore, a new evolution algorithm, particle swarm optimization, is proposed to solve radar jamming task assignment and is compared with the genetic algorithm. The simulation result shows that the algorithm has faster computing speed and fewer parameters to adjust under the same conditions compared with the genetic algorithm and it is suitable for deployment optimization of radar net.
出处
《现代防御技术》
北大核心
2009年第5期118-122,共5页
Modern Defence Technology
关键词
粒子群优化算法
雷达干扰任务分配
离散优化问题
particle swarm optimization （PSO） arithmetic
radar jamming task allocation
discrete optimization problem
