A Threat Assessment Method for Unmanned Aerial Vehicle Based on Bayesian Networks under the Condition of Small Data Sets

Abstract

The autonomous decision-making of a UAV is based on rapid and accurate threat assessment of the target. Accordingly, modeling of threat assessment under the condition of a small data set is studied in this paper. First, the operational scenario of a manned/unmanned aerial vehicle is constructed, and feature selection and data preprocessing are performed. Second, to obtain the structure, a modeling method for threat assessment is proposed based on an improved BIC score. Finally, the obtained model is applied to compute the threat probability using the junction tree algorithm. The experimental results show that the method proposed in this paper is an available method for threat assessment under the condition of small data sets.