摘要
针对目前干扰任务分配模型比较简单,在实战环境中适应性差的问题,以实战中多参数,多约束条件为基础,改进了目前的干扰任务分配模型;根据改进模型非线性,参数多,传统算法求解困难的特点,引入粒子群算法对模型求解。最后以干扰型空射诱饵弹与敌预警雷达对抗为例,对三种典型态势进行了仿真分析,结果说明了改进模型的有效性。
Aiming at the problem that existing jamming task assignment model is simpler and not suitable for the actual combat, a jamming task assignment model is improved under simple conditions based on the characteristics of more parameters and more constraints in the actual combat. Besides, particle swarm optimization is introduced to solve the model according to the features of nonlinear model, multi-parameter, and the difficulty of traditional algorithm. Lastly, three typical situations that jamming miniature air-launched decoys confront with enemy warning radars are simulated. The results illustrate the effectiveness of the model.
出处
《计算机仿真》
CSCD
北大核心
2016年第7期69-72,139,共5页
Computer Simulation
关键词
干扰任务分配
粒子群算法
干扰型空射诱饵弹
随队支援
突防
Jamming task assignment
Particle swarm optimization （ PSO ）
Jamming miniature air-launched decoy
Escort-support jamming （ESJ）
penetration
