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14 April 2022 CNN-based radar communication integrated signal sidelobe suppression method
Yinsong Zhao, Jun Hu, Shiyou Xu, Longqiu Feng
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Proceedings Volume 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021); 121780D (2022) https://doi.org/10.1117/12.2631826
Event: International Conference on Signal Processing and Communication Technology (SPCT 2021), 2021, Tianjin, China
Abstract
Radar communication waveform design is crucial for integrated radar and communication equipment, and abstracts increasing attention. The integrated radar communication waveform is usually faced with a higher sidelobe issue, compared with the single radar waveform, which will reduce the detection performance of radar. In this paper, we propose a convolutional neural network (CNN) based sidelobe suppression method for the integrated radar communication waveform. Different from the conventional method, the proposed method transforms the sidelobe suppression into a signal recognition and classification problem. The simulation results show that when the signal-to-noise ratio is not less than 3dB, this method can make the peak sidelobe ratio of matched filtering reach below -50dB, which has a great improvement compared with the traditional sidelobe suppression method.
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Yinsong Zhao, Jun Hu, Shiyou Xu, and Longqiu Feng "CNN-based radar communication integrated signal sidelobe suppression method", Proc. SPIE 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021), 121780D (14 April 2022); https://doi.org/10.1117/12.2631826
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KEYWORDS
Radar
Neural networks
Signal processing
Radar signal processing
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