Air Target Threat Assessment Method Based on Variable Weight Cloud Bayesian Network

Air Target Threat Assessment Method Based on Variable Weight Cloud Bayesian Network

연구 분야: Safety

학회: 2023 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)

In this paper, an air Air target threat assessment method based on a variable weight cloud Bayesian network (VWCBN) is proposed, which addresses the qualitative issue of air target threat levels, as most of the existing threat assessment results in focus on quantitative analysis. The proposed method enables high, medium, and low qualitative decision-making for air target threat levels. Firstly, a Bayesian network model that incorporates the attribute of air threat is constructed, assessing the threat level of air targets. Secondly, the cloud model is introduced to the Bayesian network, using it to represent the probability of correlation between nodes in the network. Then, by combining the battlefield situation information, using an improved variable weight method with Gaussian expression, the weights of target attributes are determined. Finally, based on the correlation probability and target attribute weight, the cloud model operation rules are utilized to obtain the decision of the air target threat level. Simulation results demonstrate that the proposed VWCBN method can effectively assess target threats, obtain air target threat level decisions, and further improve the utilization of battlefield information.