Radar target number estimation method based on deep residual network
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School of Electronics and Communication Engineering,Sun Yat-sen University,Shenzhen Guangdong 518107,China

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    Abstract:

    Traditional radar detection methods generally detect the target of a range cell as a single target, but do not estimate the number of targets in the range cell. Aiming at this research vacancy, a target number estimation method based on deep residual learning is proposed. The method converts the radar signal into time-frequency graph and inputs it to the trained deep residual network. The residual network can accurately estimate the number of radar targets according to the difference of time-frequency graph between single target and multiple targets. The residual network can then output an estimate of the number of radar targets. Simulation results show that this method can estimate the number of radar targets effectively.

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吴明华,饶彬,王伟.基于深度残差网络的雷达目标数量估计方法[J]. Journal of Terahertz Science and Electronic Information Technology ,2022,20(3):213~217

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History
  • Received:September 30,2021
  • Revised:November 22,2021
  • Adopted:
  • Online: March 31,2022
  • Published: