Target Threat Assessment in Air Combat with Incomplete Information

Situational information obtained in a high confrontation air combat environment is likely to be incomplete, such as data distortion, error, or even missing, which can easily lead to large deviations of partial threat assessment results at certain moments and affect subsequent decision-making. Aiming at this problem, an air combat target threat assessment method based on improved evidential network (EN) is proposed in this paper. Firstly, for the selected attribute variables that are closely related to threat assessment of air combat targets and are easy to obtain, an advantage function calculation method is designed and an evidential network model is built. Then, for the incomplete evidence information, an evidence preprocessing and correction method based on data prediction is proposed, and an evidence belief structure conversion method based on the triangular fuzzy conversion relationship is designed. Finally, the network reasoning is realized by continues-time information fusion. Simulation results show that this method can make full use of the extractable target attribute information and accurately evaluate the threat level of the enemy fighter under random and incomplete data.