Target Allocation Method of Multi-Aircraft Cooperative Air Combat Based on Improved Artificial Immune Algorithm

改进人工免疫算法的多机协同空战目标分配方法

¹ 93175 Troops, The Chinese People's Liberation Army, Changchun 130000, China
² Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an 710051, China
³ 94754 Troops, The Chinese People's Liberation Army, Jiaxing 314000, China
⁴ 95026 Troops, The Chinese People's Liberation Army, Foshan 528000, China

Received: 16 April 2018

Abstract

Aiming at the target allocation of multi-aircraft cooperative air combat, an improved artificial immune algorithm is proposed based on the modeling for comprehensive superiority function. Firstly, the random generation method and artificial construction method are used to create two initial populations, which ensure the diversity of the initial populations; following is to evolve the populations by adopting two different selection, crossover and mutation operations; then, the designed new immigration operator is used to exchange information among the populations, which further increases the diversity of the populations and improves the search efficiency. Finally, the comparison of the improved artificial immune algorithm with the traditional artificial immune algorithm had been made. Simulation results show that the improved artificial immune algorithm can effectively improve the premature convergence problem, and the search efficiency, the optimal allocation scheme is obtained, which is suitable for target allocation problem of multi-aircraft cooperative air combat and meet the actual operational requirements.

摘要

针对多机协同空战目标分配问题，在我方综合优势函数建模的基础上，提出了一种改进人工免疫算法。首先采用随机生成法和人工构造法创建2个初始种群，保证了初始种群的多样性；然后采用2种不同的选择、交叉、变异操作进行进化；接着采用设计的新移民算子进行种群间信息交换，进一步增加种群多样性，提高搜索效率。最后设计实验将改进人工免疫算法与3种类型的人工免疫算法进行了对比。仿真结果表明：改进人工免疫算法能够有效改善早熟收敛问题，提高搜索效率，获得最优分配方案，适用于多机协同空战目标分配问题，满足实际作战需求。