Unmanned Swarm System Situation Awareness Based on Dynamic Bayesian Network
Ao Liu, Liang Geng, Yu Zhen An, Haipeng Wang, Hao Liu · 2022 IEEE International Conference on Unmanned Systems (ICUS) · 2022
In a multidimensional and complex battlefield environment, unmanned swarm system can determine the threat level of surrounding targets through situation awareness to assist in guiding strategic decision-making. This paper constructs a model of unmanned swarm system situation awareness based on Dynamic Bayesian Network. By analyzing the threat situation caused by the different behavior states of unmanned swarm system, the time-varying probability of different behavioral intentions is calculated to assist decision-making more effectively. The advantages of this model are comprehensively considering the changes in the time dimension and the probability characteristics of multiple state factors of unmanned swarm system. And the effectiveness of the model is verified by experimental simulation, which indicates the strong application value of the model.