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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