Title: Multi-source Information Data Fusion Method under Complex Battlefield Situation
Abstract: Abstract Under complex battlefield situation, the situation information is instantaneous and changeable. The uncertain information always causes difficulty in acquisition information and miscalculation, and lead to low efficiency and poor accuracy for aircraft situation awareness. In order to solve the problem, in this paper it proposes a deep-learning based multi-sensor situation awareness data fusion method. With data acquitted from multiple sensors in multi-band and multi-angle, it realizes multi-sensor information data fusion by comparing and analysing of two AI data fusion methods that one is based on classical evidence theory and the other is based on deep learning. The simulation results indicate that the deep-learning based data fusion method presents higher efficiency in dealing with the environment information fusion with large evidence conflict.