基于改进NSGA-III算法的多无人机协同目标分配  

Multi-UAV Cooperative Target Assignment Based on Improved NSGA-III Algorithm

作　　者：王爽宇 申庆茂 孙铭阳 唐爽 甄子洋[1] Wang Shuangyu;Shen Qingmao;Sun Mingyang;Tang Shuang;Zhen Ziyang(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China;Second Military Representative Office of Air Force Equipment Department in Beijing Area,Beijing 100000,China;Institute of Intelligent Operation Research and Information Security of Aerospace Science and Technology,Wuhan 430000,China)

机构地区：[1]南京航空航天大学自动化学院,南京211106 [2]空军装备部驻北京地区第二军事代表室,北京100000 [3]航天科工智能运筹与信息安全研究院,武汉430000

出　　处：《航空兵器》2024年第4期100-111,共12页Aero Weaponry

基　　金：国家自然科学基金项目(61973158);南京航空航天大学前瞻布局科研专项(1003-ILA22064)。

摘　　要：武器-目标分配问题是战场环境下无人机对敌方执行打击任务的关键,其目的是基于目标的威胁、价值和我方武器的毁伤概率,寻找合理的武器目标分配方案,以提高作战效率。针对当前多目标优化算法解决静态武器-目标分配问题时收敛速度慢、收敛稳定性差,难以适应当前战场高度实时性的问题,提出一种改进的基于参考点的非支配排序遗传算法。通过二进制编码打击方案并优化初始种群,引入自适应变异与交叉策略以及种群寻优更新策略,基于对战场态势进行评估得到的威胁矩阵和优势矩阵,种群多次迭代后生成目标打击方案。最后计算满足约束条件的Pareto解集,并将Pareto前沿中的相对最优解作为多无人机的打击方案。多次实验证明,在较好情况下改进算法相比于原始算法的收敛时间减少46.74%,目标威胁值降低50.5%,总飞行航程减少26.46%,杀伤目标数增加11.76%,证明该算法在解决多无人机空对地打击任务目标分配问题时具有合理性和高效性。The weapon-target assignment problem is the key to the combat mission of the UAV against the enemy in the battlefield environment.The purpose is to find a reasonable weapon target assignment scheme based on the threat,value and damage probability of the target,so as to improve the combat efficiency.Aiming at the problem that the current multi-objective optimization algorithm has slow convergence speed and poor convergence stability when solving the static weapon-target assignment problem,and it is difficult to adapt to the high real-time performance of the current battlefield,an improved non-dominated sorting genetic algorithm based on reference points is proposed.The initial population is optimized by binary coding attack scheme,and adaptive mutation and crossover strategy as well as population optimization update strategy is introduced.Based on the threat matrix and advantage matrix obtained by evaluating the battlefield situation,the target attack scheme is generated after multiple iterations of the population.Finally,the Pareto solution set satisfying the constraint condition is calculated,and the relative optimal solution in the Pareto frontier is taken as the attack scheme of multi-UAV.Multiple experiments show that under good conditions,the improved algorithm reduces convergence time by 46.74%,reduces target threat value by 50.5%,reduces total flight range by 26.46%,and increases the number of killing targets by 11.76%compared with the original algorithm.It is proved that the algorithm is reasonable and efficient in solving the problem of target assignment of multi-UAV air-to-ground strike mission.

关 键 词：对地打击 多无人机 武器目标分配 多目标优化 NSGA-III PARETO解 

分 类 号：TJ760[兵器科学与技术—武器系统与运用工程] V279[航空宇航科学与技术—飞行器设计]