LPI radar signal recognition based on time-frequency reassignment algorithm

In view of the problems of low probability of acquisition (LPI) radar signal recognition in low signal-to-noise ratio (SNR) and complex network model, an LPI radar signal recognition method based on time-frequency reassignment and multi-scale residual network was proposed. The time-frequency reassignment approach is used to enhance the signal's aggregation based on the Wigner-Ville distribution (WVD). The resulting time-frequency distribution image is then fed into the multi-scale residual network to finish the signal's categorization. In addition, the complex electromagnetic environment simulation was completed by constructing a multi-path Rice-fading channel. According to the experimental results, when the SNR is −8 dB, the suggested approach can achieve 94% recognition accuracy for a total of 13 different types of typical LPI radar modulation patterns, including Costas, Frank, P1～P4, etc. Compared with other methods, it has better recognition performance at a low signal-to-noise ratio.