Volume 50 Issue 3
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YANG J,HAO X H,CHEN Q L. Automatic recognition method of multi-radar signals based on multi-domain features[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(3):931-939 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0294
Citation: YANG J,HAO X H,CHEN Q L. Automatic recognition method of multi-radar signals based on multi-domain features[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(3):931-939 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0294

Automatic recognition method of multi-radar signals based on multi-domain features

doi: 10.13700/j.bh.1001-5965.2022.0294
Funds:  National Natural Science Foundation of China (61871414)
More Information
  • Corresponding author: E-mail:haoxinhong@bit.edu.cn
  • Received Date: 29 Apr 2022
  • Accepted Date: 29 Jun 2022
  • Available Online: 03 Aug 2022
  • Publish Date: 03 Aug 2022
  • In complex electromagnetic environments, simultaneous signal transmission of multiple radars in similar frequency bands can cause overlapping of reconnaissance’s received signals in the time and frequency domains. To address this problem, an automatic modulation recognition (MR) method with a low signal-to-noise ratio (SNR) is proposed. The energy of the received signal is concentrated on the respective Doppler frequency through the row FFT transformation between the received pulses to achieve the separation of multiple intercepted signals. The Wigner-Ville distribution (WVD) and ambiguity function (AF) of each signal are simultaneously sent to the trained residual neural network (ResNet) as two layers of an image to solve the problem of low recognition accuracy when some types of signals only use a single time-frequency distribution. Theoretical analysis and simulation results show that the proposed method can not only effectively separate multiple radar signals overlapping in the time and frequency domains, but also accurately identify their modulation modes with the SNR of −10 dB.

     

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