Cooperative Combat Coalition Formation of Heterogeneous UAV Swarm Based on Dynamic Consensus-based Grouping Algorithm

doi:10.12382/bgxb.2023.0914

Abstract

Abstract:

The formation of a heterogeneous unmanned aerial vehicle (UAV) swarm cooperative combat coalition under dynamic, unknown or contested conditions is a crucial aspect of practical UAV swarm operations. A decision control process framework for UAV swarm based on the dynamic consensus-based grouping algorithm (DCBGA) is constructed. A communication networking model with communication constraints is designed for UAV swarm, and a dynamic adaptive mechanism is introduced to effectively cope with high dynamic task scenarios. Based on the “operation loop” theory, the aggregation effect of non-linear combat effectiveness of heterogeneous units under the network architecture is described, and included in the global performance function to guide the formation of the heterogeneous UAV cooperative combat coalition. The coalition formation process is divided into three stages: target selection, consensus, and information and state update. The dynamic consensus-based grouping algorithm is used to support the UAV swarm in completing the information decision control of each stage from the bottom up. Simulated results show that the proposed algorithm system can effectively promote the heterogeneous UAV swarms to realize the formation of combat coalitions and complete the coordinated combat missions, demonstrating good dynamic adaptability and scalability, and exhibiting better resilience in contested environments.

Key words: heterogeneous unmanned aerial vehicle swarm, coalition formation, combat effectiveness, distributed framework, consensus, resilience

CLC Number:

V249

PAN Zishuang, SU Xichao, HAN Wei, LIU Wenlin, YU Dazhao, WANG Jie. Cooperative Combat Coalition Formation of Heterogeneous UAV Swarm Based on Dynamic Consensus-based Grouping Algorithm[J]. Acta Armamentarii, 2024, 45(9): 3177-3190.

Figures/Tables 9

Fig.1 Process decomposition of heterogeneous UAV swarm combat missions based on coalition formation

Fig.2 Construction of swarm communication network

Table 1 Parameters for targets

序号	任务类型	火力需求	最佳战位/km	名义回报
1	侦察-攻击	1-4	0.53-0.30	0.4
2	侦察-攻击	1-5	0.54-0.32	0.5
3	侦察-攻击-干扰	1-5-6	0.54-0.36-0.24	1.8
4	侦察-攻击-干扰	1-3-4	0.55-0.40-0.20	1.5

Fig.3 Mission execution of UAV swarm at different moments

Fig.4 Sensitivity analysis

Fig.5 Improvement of forgetfulness characteristic

Fig.6 Improvement of confusing characteristic

Fig.7 Mission execution of UAV swarm at different moments

Fig.8 UAV swarm integrated mission execution capability curve

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