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

Authors

• Yelei Zhu, Army Command College, Nanjing 210008, China
• Shoulin Shen, Army Command College, Nanjing 210008, China
• Jiang Zhu, Army Command College, Nanjing 210008, China
• Chuanhua Wen, Army Command College, Nanjing 210008, China

Abstract

Abstract: Intelligent unmanned aerial vehicle swarm combat exhibits multi-scale characteristics of microlevel 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.

Recommended Citation

Zhu, Yelei; Shen, Shoulin; Zhu, Jiang; and Wen, Chuanhua (2026) "Multi-scale Modeling Method for Intelligent Unmanned Aerial Vehicle Swarm Combat," Journal of System Simulation: Vol. 38: Iss. 7, Article 5.
DOI: 10.16182/j.issn1004731x.joss.26-0001
Available at: https://dc-china-simulation.researchcommons.org/journal/vol38/iss7/5

First Page

1849

Last Page

1869

CLC

TP391.9

Recommended Citation

Zhu Yelei, Shen Shoulin, Zhu Jiang, et al. Multi-scale Modeling Method for Intelligent Unmanned Aerial Vehicle Swarm Combat[J]. Journal of System Simulation, 2026, 38(7): 1849-1869.

Corresponding Author

Shen Shoulin

DOI

10.16182/j.issn1004731x.joss.26-0001