A Multimodal EEG Identification Method for Complex Aerospace Target Recognition

Accurate recognition of aerospace targets in complex flight scenarios is the primary crucial link to achieve intelligent decision-making and control of aircraft. In the face of open complex flight environments with variants, camouflage and deception, traditional target recognition methods cannot meet the needs of practical applications, and the performance of computer automatic image analysis methods is far from human recognition ability. This paper innovatively proposes a complex aerospace target recognition method based on multimodal EEG identification: proposes EEG signal acquisition and pre-processing techniques under complex visual stimulation, and accurately obtains EEG representation information under relevant visual stimulation; design a multi-wavelet analysis-based time-frequency feature extraction method and multi-scale time-domain feature extraction technology, and obtain effective discriminatory EEG features under different stimulation. The method is designed to obtain multimodal EEG features with effective discriminative ability under different stimuli. The experimental results show that the proposed method can effectively identify the target of interest, which is of great significant for promoting the development of intelligent perception and recognition models for new generation unmanned systems.