系统仿真学报 ›› 2026, Vol. 38 ›› Issue (7): 1849-1869.doi: 10.16182/j.issn1004731x.joss.26-0001

• 论文 • 上一篇    下一篇

一种面向智能无人机集群作战的多尺度建模方法

朱烨雷, 沈寿林, 朱江, 闻传花   

  1. 陆军指挥学院,江苏 南京 210008
  • 收稿日期:2026-01-03 修回日期:2026-03-15 出版日期:2026-07-28 发布日期:2026-07-31
  • 通讯作者: 沈寿林
  • 第一作者简介:朱烨雷(1985-),男,博士生,研究方向为机器学习与人工智能、军事运筹与作战实验。
  • 基金资助:
    国家自然科学基金(71401177)

Multi-scale Modeling Method for Intelligent Unmanned Aerial Vehicle Swarm Combat

Zhu Yelei, Shen Shoulin, Zhu Jiang, Wen Chuanhua   

  1. Army Command College, Nanjing 210008, China
  • Received:2026-01-03 Revised:2026-03-15 Online:2026-07-28 Published:2026-07-31
  • Contact: Shen Shoulin

摘要:

智能无人机集群作战呈现出微观战术自主性、中观资源约束性和宏观网络协同性的多尺度特征。针对单一尺度建模方法难以同时刻画个体决策细节、资源流动过程与体系协同机制的问题,提出一种融合多智能体建模、系统动力学与复杂网络理论的多尺度建模方法。通过设计6种形式化耦合算子实现跨层信息映射,建立了基于主从时钟与混合同步的时间推进机制,并给出了误差有界性分析。在仿真平台实现原型系统,通过红蓝无人机集群对抗场景开展消融和战术涌现实验,结果证实多尺度建模方法相比单一尺度方法具有显著优势,为智能无人机集群作战系统建模提供了一种可行的工程化实现途径。

关键词: 智能无人机集群, 多尺度建模, 多智能体, 系统动力学, 复杂网络, 战术涌现

Abstract:

Intelligent unmanned aerial vehicle swarm combat exhibits multi-scale characteristics of micro-level tactical autonomy, meso-level resource constraints, and macro-level network collaboration. In view of the problem that a single-scale modeling method is difficult to simultaneously characterize individual decision-making details, resource flow process, and system collaboration mechanism, a multi-scale modeling method integrating multi-agent modeling, system dynamics, and complex network theory was proposed. By designing six formal coupling operators to achieve cross-layer information mapping, a time progression mechanism based on a master-slave clock and hybrid synchronization was established, and a proof of error boundedness was provided. A prototype system was implemented on a simulation platform, and ablation and tactical emergence experiments were conducted through a red-blue unmanned aerial vehicle swarm confrontation scenario. The results confirm that the multi-scale modeling method has significant advantages over the single-scale method, which provides a feasible engineering implementation path for the modeling of intelligent unmanned aerial vehicle swarm combat systems.

Key words: intelligent unmanned aerial vehicle swarm, multi-scale modeling, multi-agent, system dynamics, complex network, tactical emergence

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