基于深度学习时序特征增强的海杂波抑制方法OA

To overcome the limitations of traditional approaches in suppressing sea clutter which displays complex,non-stationary,non-Gaussian distributions and strong temporal correlation,this paper introduces RTFEN(Radar Temporal Feature Enhancement Network),a deep learning method that improves temporal feature extraction.The technique employs a temporal compression module to suppress clutter via space-time filtering,a bidirectional ConvLSTM to model motion differences between targets and clutter,and a temporal attention mechanism to adaptively enhance target information in key frames.Experimental results show that the proposed method can effectively enhance sea-clutter suppression performance.