摘要
雷达干扰任务分配是雷达对抗仿真的重要组成部分,雷达干扰任务分配是否合理直接影响电子对抗作战效能。由于常规优化算法相对复杂、计算时间较长,用来解决此问题难以满足实时仿真的要求。针对这一问题,提出适用于解决雷达干扰任务分配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速度快、精度较高的优势,较好地满足了雷达对抗实时仿真的要求。
Radar jamming task assignment is one of the most important functions of EW simulation system. The result of radar jamming task assignment has great influence on the EW effect. At present, the existing optimization algorithm has difficulty in meeting the demand of simulation for its complexity and long computing time. In view of this problem, a new evolution algorithm, particle swarm optimization, is adopted to solve radar jamming task assignment problem on the basis of studying the problem, and the algorithm is compared with the Genetic algorithm. The simulation result shows that the algorithm has higher computing speed and precision under the same condition compared with the Genetic algorithm, so it is more suitable for solving radar jamming task assignment problem.
出处
《计算机仿真》
CSCD
2008年第12期27-30,共4页
Computer Simulation
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 assignment
Discrete optimization problem