@article{JI2025, 
author = {Libin JI and Yan ZHU and Tianshu CUI and Dong WANG and Yonghui HUANG},
title = {LPI radar signal recognition based on time-frequency reassignment algorithm},
year = {2025},
journal = {Journal of Beijing University of Aeronautics and Astronautics},
volume = {51},
number = {4},
pages = {1324-1331},
keywords = {low intercept probability radar, signal recognition, time-frequency reassignment, multi-scale residual network, modulation style},
url = {https://www.sciopen.com/article/10.13700/j.bh.1001-5965.2023.0218},
doi = {10.13700/j.bh.1001-5965.2023.0218},
abstract = {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.}
}