基于IMOSFLA的有人/无人战斗机协同空战火力分配方法

Solving method based on IMOSFLA for weapon-target assignment in cooperative air combat of manned vehicle and unmanned vehicle

针对有人/无人战斗机协同空战中的火力分配问题,建立了以目标总存活概率最小和武器消耗数量最少的火力分配多目标优化模型,并提出一种改进的多目标蛙跳算法用于求解问题的Pareto最优解集。该改进算法充分利用混洗蛙跳算法收敛速度快、收敛精度高的算法优势进行全局寻优,利用自适应网格法对非劣解进行维护和更新,并在青蛙种群的全局进化过程中引入Tent混沌变异以避免算法早熟收敛。为便于从求解得到的Pareto最优解集中选择出最优火力分配方案,提出了一种最优火力分配方案的自主选择规则。最后通过仿真实验验证了所提方法的可行性和有效性。实验结果表明,所提方法能有效求解有人/无人战斗机协同空战中的火力分配问题。

Aiming at the weapon-target assignment （ WTA ） problem in cooperative air combat of manned vehicle and un- manned vehicle, this paper established a multi-objective optimization mathematical model, which included minimize the total survival probability of all targets and minimize the consumption of the air-to-air missiles, then put forward an improved muhi- objective shuffled frog leaping algorithm（SFLA） ,which referred to as IMOSFLA, to solve the Pareto optimal solutions of this problem. The IMOSFLA made full use of the superiority of the shuffled frog leaping algorithm, high convergence speed and high convergence precision, to execute the global optimization firstly. Then the IMOSFLA used the adaptive grid algorithm to maintain and update the Pareto solutions. And then it introduced a kind of Tent chaotic mutation into the process of the global evolution of the frog species to avoid the IMOSFLA falling into the premature convergence. In addition, it defined an autono- mous selection rule for optimum weapon-target allocation from the Pareto optimal solution set. Finally, the simulation experi- ments verified the feasibility and effectiveness of the proposed method. The experimental results show that the proposed method can solve the weapon-target assignment in cooperative air combat of manned vehicle and unmanned vehicle effectively.