Abstract
To solve the problem of the low recognition rate of the existing methods at low signal-to-noise ratio (SNR), we propose a novel method of radar signal waveform recognition. In this method, we extract the time-frequency images (TFIs) of radar signals through Cohen class time frequency distribution. Then, we introduce convolutional denoising autoencoder (CDAE) to denoise and repairs the TFIs. Finally, we build a convolutional neural network (CNN) to identify the TFIs of radar signals. Simulation experiment shows that the proposed method can identify 12 kinds of radar signal waveforms, and the overall probability of successful recognition (PSR) is 95.4% when the SNR is −7 dB.
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References
Latombe G, Granger E, Dilkes FA. Fast learning of grammar production probabilities in radar electronic support. IEEE Trans Aerosp Electron Syst. 2010;46(3):1262–89.
Gupta M, Hareesh G, Mahla AK. Electronic warfare: issues and challenges for emitter classification. Defence Sci J. 2011;61(3):228–34.
Zeng D, Zeng X, Cheng H, Tang B. Automatic modulation classification of radar signals using the Rihaczek distribution and Hough transform. IET Radar Sonar Navig. 2012;6(5):322–31.
Zhou D, Wang X, Tian Y, Wang R. A novel radar signal recognition method based on a deep restricted Boltzmann machine; 2017
Zhang M, Diao M, Guo L. Convolutional neural networks for automatic cognitive radio waveform recognition. IEEE Access. 2017;5:11074–92.
Jain V, Seung HS. Natural image denoising with convolutional networks. In: International conference on neural information processing systems; 2008. p. 769–76
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Liu, Z., Mao, X., Deng, Z. (2020). Radar Signal Waveform Recognition Based on Convolutional Denoising Autoencoder. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_91
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DOI: https://doi.org/10.1007/978-981-13-6504-1_91
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