基于SAGA的协同多目标攻击决策

以超视距协同空战为背景,在对每个目标分配一枚导弹攻击的模式下,研究了协同多目标攻击空战决策问题.首先,基于对空战威胁态势的分析,将协同多目标攻击决策问题转化为导弹目标攻击分配的优化问题并建立其攻击效能评估模型.然后,提出将模拟退火遗传算法(SAGA)用于该问题的寻优,算法中个体采用整数编码,并采用非常规的交叉与变异操作产生新的个体.在进化结束后,通过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对最优分配方案的搜索效率明显优于单纯的遗传算法.

Air combat decision-making for cooperative multiple target attack based on SAGA

With the background of cooperative air combat under the Beyond Visual Range(BVR) condition,decision-making problem for Cooperative Multiple Target Attack(CMTA) is investigated under the attack mode of each target being assigned one missile.First,based on the analysis on air combat threat situation,decision-making for CMTA is converted into a Missile-Target Assignment(MTA) optimization problem with the establishment of the attack effectiveness evaluation model.Then,Simulated Annealing Genetic Algorithm(SAGA) is presented to search for the optimal solution to the MTA problem.In SAGA,individual chromosome encoded with integer,and unconventional crossover and mutation operators are employed to generate new individuals.After the evolutionary process stopped,the final decision-making solution of CMTA is derived from the best missile-target assignment individual.Simulation results show that the proposed method is more effective than pure Genetic Algorithm(GA) to find out the optimal assignment solution.