多UCAV协同目标攻击决策  

Target attack decision-making for cooperating multi-UCAV

作　　者：宋磊[1] 黄长强[1] 吴文超[1] 李望西[1] 轩永波[1] 

机构地区：[1]空军工程大学工程学院,陕西西安710038

出　　处：《系统工程与电子技术》2011年第7期1548-1552,共5页Systems Engineering and Electronics

基　　金：国家高技术研究发展计划(863计划)(2009AAJ205);空军工程大学研究生科技创新计划(DX2010108)资助课题

摘　　要：针对多无人作战飞机(unmanned combat aerial vehicle,UCAV)攻击多目标,研究了多UCAV协同攻击决策问题。建立了目标毁伤模型、UCAV损耗模型和时间协同模型,并通过加权求和将三者转化为单一目标函数,进而转化为单目标问题进行求解。提出了一种离散微粒群优化(discrete particle swarm optimization,DPSO)算法,在微粒群优化算法框架内重新定义了微粒的位置、速度及相关操作。建立了微粒与实际问题的映射关系,进而使DPSO算法适合于求解多UCAV协同目标攻击决策问题。仿真结果表明,DPSO算法易于实现,能够较好地解决基于时间协同的多UCAV目标攻击决策问题。Target attack decision-making for cooperating multiple unmanned combat aerial vehicle （multi- UCAV） is discussed to solve the problem of attacking multi-target. Models of target damage, UCAV attritions and timing cooperation are formulated. And these models are translated into a single target function and then proceed to single-target optimization problem. A new discrete particle swarm optimization （DPSO） algorithm is pro- posed, and particles~ position, speed and relative operations are newly defined within a framework of the particle swarm optimization （PSO） algorithm. A mapping rule is established between particles and the problem so as to make DPSO algorithm suitable for target attack decision-making. The simulation results show that the algorithm is simple and could effectively solve the problem of target attack decision-making for multi-UCAV based on timing cooperation.

关 键 词：多无人作战飞机 目标攻击决策 离散微粒群优化 时间协同 

分 类 号：V279[航空宇航科学与技术—飞行器设计]