航空学报 > 2020, Vol. 41 Issue (S2): 724257-724257   doi: 10.7527/S1000-6893.2020.24257

空战中机群编队分层优化算法

冉华明, 熊蓉玲   

  1. 中国电子科技集团公司第十研究所 航空电子信息系统技术重点实验室, 成都 610036
  • 收稿日期:2020-04-20 修回日期:2020-05-20 发布日期:2020-06-04
  • 通讯作者: 冉华明 E-mail:ranhuaming7245@163.com
  • 基金资助:
    国防科技创新特区项目

Hierarchical optimization algorithm for air fleet formation in air-combat

RAN Huaming, XIONG Rongling   

  1. Key Laboratory of Avionic Information System Technology, The 10 th Research Institute of China Electronics Technology Group Corporation, Chengdu 610036, China
  • Received:2020-04-20 Revised:2020-05-20 Published:2020-06-04
  • Supported by:
    National Defence Pre-research Foundation

摘要: 针对机群编队优化计算复杂的问题,提出了一种分层优化算法。根据敌我双方的距离、角度、速度以及飞机导弹、雷达的性能,建立了多机协同任务分配模型。根据空战中常用的基本飞机队形,对敌方机群编队进行分层,对每层分别计算己方对选取各种基本队形时的任务分配结果和队形优化优势值,通过比较得到己方机群编队的每层最优队形,当得到己方每层的最优队形之后,将己方每层最优队形进行组合解码就可得到己方机群编队的最优队形。仿真结果表明该方法能有效地解决机群编队队形优化问题,并且该算法具有较好的实时性。

关键词: 机群编队, 队形优化, 任务分配, 分层优化, 队形编码

Abstract: To solve the problem of computing complexity in air fleet formation optimization, this paper proposes a hierarchical optimization algorithm. A collaborative task allocation model was established based on the distance, the angle, the velocity, and the performance of the missiles and radars of both sides. The air fleet formation of the enemy was layered according to the basic aircraft formations usually adopted in air combat. For each layer, when our formations of this layer select a variety of basic formations, the task allocation results and formation optimization advantages were calculated, and the optimal formations of this layer in our air fleet were then calculated by comparison. When all the optimization formations of each layer were obtained, the optimal formation of our air fleet can be obtained through combinational decoding of the optimal formations of each layer. The simulation results demonstrate that this method can effectively solve the fleet formation optimization problem with good real-time performance.

Key words: air fleet formation, formation optimization, task allocation, hierarchical optimization, fleet coding

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