Advanced Method for Polyphase Coded Radar Signal Classification and Recognition Based on Deep Learning

An advanced method based on modified wavelet transform and deep learning was proposed to reduce training time and improve the recognition accuracy of polyphase-coded radar signals in low signal-to-noise ratios. The proposed method includes two stages. In the first step, the feature parameters of polyphase-coded radar signals (Barker, Frank, P1, Px, Zadoff-Chu) are extracted. Then, the classification and recognition of polyphase-coded radar signals are implemented using Deep learning. The tested results show that the proposed method exceeds the existing methods based on machine learning and artificial intelligence in terms of time training and accuracy.