集群智能与协同控制

基于仿真的蜂群体系对抗效能评估方法

  • 王晓悦 ,
  • 王珣 ,
  • 王永贞 ,
  • 费腾 ,
  • 刘大卫
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  • 1. 北京理工大学 宇航学院,北京 100081;
    2. 中国兵器科学研究院,北京 100089;
    3. 北京理工大学 集成电路与电子学院,北京 100081;
    4. 432178部队科创中心,北京 100020;
    5. 辽沈工业集团有限公司,沈阳 110045

收稿日期: 2022-01-10

  修回日期: 2022-02-11

  网络出版日期: 2022-05-19

基金资助

国家级项目

Evaluation method for combat effectiveness of task-based simulated UAV swarm system

  • WANG Xiaoyue ,
  • WANG Xun ,
  • WANG Yongzhen ,
  • FEI Teng ,
  • LIU Dawei
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  • 1. School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China;
    2. China Research and Development Academy of Machinery Equipment, Beijing 100089, China;
    3. School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China;
    4. Science and Technology Innovation Center of 32178 Army, Beijing 100020, China;
    5. Liao Shen Industries Group Co., Ltd, Shenyang 110045, China

Received date: 2022-01-10

  Revised date: 2022-02-11

  Online published: 2022-05-19

Supported by

National Level Project

摘要

随着群体智能技术的深入研究和无人(UAV)蜂群系统的军事运用,迫切需要检验评估蜂群体系对抗战术战法、技术指标和群体智能算法等的核心能力。为改变单纯依靠实装试验高成本、难度大的验证现状,急需开展基于任务级的数字仿真推演方法,研究面向蜂群体系对抗的仿真评估手段。本文面向现有无人蜂群技术现状和应用方向构设了无人蜂群体系典型作战场景,开发了任务级仿真平台扩展工具,建立了环境要素模型和实体模型,结合蜂群作战效能评估目的研提评估指标体系,推导评估计算模型,形成了蜂群作战效能评估方法,开展了全流程仿真推演,并依托蒙特卡洛收敛结果数据获取了蜂群体系对抗结果。提出的蜂群体系仿真与评估方法初步打通了“军事需求-体系对抗仿真-作战效能评估”作战能力评估生成与评价链路。

本文引用格式

王晓悦 , 王珣 , 王永贞 , 费腾 , 刘大卫 . 基于仿真的蜂群体系对抗效能评估方法[J]. 航空学报, 2022 , 43(S1) : 726937 -726937 . DOI: 10.7527/S1000-6893.2022.26937

Abstract

With the in-depth study on the Unmanned Aerial Vehicle (UAV) swarm intelligence technology and the application of unmanned bee UAV swarm system in the military field, it is urgently needed totest and evaluate the core capabilities of the system, such as combat tactics, technical indicators and UAV swarm intelligence algorithms. In order to change the high cost and difficult verification status quo of relying solely on practical tests, it is necessary to explore the task-based digital simulation deduction method for typical combat scenarios, and build a simulation evaluation method to improve the combat effectiveness of the UAV swarm system. In view of the status quo and applications of the existing unmanned bee colony technology, this paper constructs a typical combat scenario of the unmanned bee colony system, develops a task-based simulation platform extension tool, and establishes an environmental element model and an entity model. In combination with the purpose of the bee swarm combat effectiveness evaluation, the assessment index system is developed, the evaluation calculation model is derived, an evaluation method for the combat effectiveness of the UAV swarm is developed and the all-process simulation deduction is carried out. The combat results of the bee colony system are derived based on the Monte Carlo convergence results. With the simulation and evaluation method for the UAV swarm system proposed in this paper, the combat capability evaluation generation and evaluation link of “military requirements-system combat simulation-combat effectiveness evaluation” are preliminarily established.

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