Air-Combat Decision-Making for UAVs Cooperatively Attacking Multiple Targets

摘要

中文摘要：针对超视距空战中多架无人机对空中的多个敌对目标进行协同攻击的决策问题进行了研究。首先，对空战威胁态势进行了分析，基于对各攻击目标至少分配一枚导弹的原则，将协同多目标攻击决策问题转化为导弹目标攻击配对的优化问题并建立其攻击效能评估模型。然后，提出了一种模拟退火遗传算法用于该决策问题的寻优。最后，通过所得最佳导弹目标分配个体求得最终协同攻击决策方案。仿真结果表明所提出的算法能有效地求解协同多目标攻击决策问题，其对最优解的搜索效率明显优于单一的遗传算法。英文摘要：Abstract: Considering a Beyond Visual Range (BVR) air combat scenario with a group of UAVs versus multiple hostileairborne targets, the decision-making problem for Cooperative Attack on Multiple Targets (CAMT) was investigated. First,the air combat threat situation was analyzed. Based on the principle of each target to be attacked at least being assigned onemissile, the decision-making for CAMT was converted into a Missile-Target Assignment (MTA) optimization problem with theestablishment of the attack effectiveness evaluation model. Then, a Simulated Annealing Genetic Algorithm (SAGA) wasproposed to find out the optimal solution to the MTA problem. Finally, the final decision-making solution to the CAMT wasderived from the obtained best missile-target assignment individual. Simulation results show that the proposed method ismore effective than Genetic Algorithm (GA) to deal with the decision-making problem for CAMT.