Active Deception Jamming Recognition in the Presence of Extended Target

Accurate sensing of the main-lobe active deception jamming is critical for radar anti-jamming and extended target detection in complex electromagnetic environment. This letter therefore deals with the problem of multiple active deception jamming recognition in extended target settings. A residual convolutional neural network with attention mechanism-based radar active deception jamming recognition algorithm is proposed leveraging a hybrid model to capture much rich features through multi-domain feature fusion. The proposed method can outperform state-of-the-art methods in terms of recognition accuracy, model size, and convergence speed. Experimental results demonstrate its effectiveness and robustness.