摘要
协同空战中目标分配是否合理有效决定着作战效能的大小,已经成为一个核心决策问题。针对战场态势复杂多变,目标分配受到多种限制,对实时性要求高的问题,提出了优化策略。综合考虑空战中的作战效能和作战代价,构建目标函数,根据实战环境建立约束条件。为了满足现代空战实时快速的要求,通过引入遗传算法交叉算子和Bolzmann选择策略的方法,对人工蜂群算法进行改进,既提高了算法的搜索能力,又保证了算法的收敛速度。仿真分析表明:目标分配模型合理有效,目标分配效能得到了优化,对协同空战具有较好的实用价值。
Target allocation is a core decision question for cooperative air combat,which decides the combat effectiveness. Optimization strategy is proposed to solve the problem that battle situation is complex,various target allocation is restricted and demand for real time is high. The target function is established,synthetically considering combat effectiveness and combat cost. Restraint condition is based on actual environment. In order to satisfy the demand for real time and fast air combat,artificial bee colony algorithm is modified through bringing in genetic algorithm cross operator and Bolzmann selection strategy. It not only improves the search ability of algorithm,but also assures the convergence speed of algorithm. The result indicates that target allocation model is reasonable and the target allocation effectiveness is optimized,it has practical value for cooperative air combat.
出处
《传感器与微系统》
CSCD
2016年第11期40-43,共4页
Transducer and Microsystem Technologies
关键词
协同空战
目标分配
优化策略
改进人工蜂群算法
cooperative air combat
target allocation
optimization strategy
modified artificial bee colony algorithm
