Hybrid Variable Structure DBN Mission Decision-Making Method for UAV Swarm

Abstract

To cope with the dynamic mission decision-making issue in complex environments for UAV swarm, a hybrid variable structure-based dynamic Bayesian network (HVSDBN) inference decision-making method is proposed. Firstly, the UAV swarm mission decision-making model is established to assess the UAV swarm state and threat state accurately. To further improve the accuracy of decision-making, the threat assessment model and swarm state assessment model are built by using mixed continuous and discrete variables, respectively. Furthermore, a dynamic HVSDBN decision-making algorithm based on hybrid performance-capability parameters is proposed, which can adjust the structure of the decision model according to the priori information and observation data to improve the adaptability of the solution strategy. Simulation results demonstrate that, the HVSDBN method can im-prove the variance of decision results by 25.03% compared with traditional method, which effectively improves the accuracy of UAV swarm mission decision-making under complex dynamic environment.