Fast Recognition of Pull-Off Jamming Using LSTM

Facing the complex electromagnetic environment, the fast and precise recognition of the type of jamming singals plays an indispensable role for rader to achieve effective electonic counter-counermeasures (ECCM). The implementation of pull-off jamming can be considered as a gradually separation of the true and false targets in the tracking gate of the radar. Thus the pull-off jamming signals can be recognized through a Long Short Term Memory (LSTM) network based on automatic features extraction and sequence dependency learning. This paper considers the signal sequences in the tracking gate as the input of the exploited LSTM model. Owing to the dependencies between signal at each frames, our method is capable of recognizing pull-off jamming at the early stage of jamming. Experimental results show that the proposed method can recognize the pull-off jamming quickly and accurately and has excellent generalization performance. Therefore, ECCM for radar against the pull-off jamming became more effective.