Proposed deep neural network ARTRNet for automatic target recognition for FMCW radar

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Authors

  • Nguyen Van Tra (Corresponding Author) Institute of Radar, Academy of Military Science and Technology
  • Nguyen Truong Son Institute of Radar, Academy of Military Science and Technology
  • Nguyen Hoang Viet Nhà máy Z181, Tổng cục Công nghiệp Quốc phòng

DOI:

https://doi.org/10.54939/1859-1043.j.mst.84.2022.24-31

Keywords:

FMCW; Radar; Range; Azimuth; Doppler; Object detection; Deep learning.

Abstract

 In this paper, we propose a deep learning neural network (named ARTRNet) that automatically recognizes radar targets based on the characteristic signature of radar cross section and Doppler frequency of target in the reflected signal. The raw data input to ARTRNet is 3D formatted with distance - azimuth - frequency information. The author proposes an improvement of the loss function in the neural network training process to improve the target recognition performance of the model.

References

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Published

28-12-2022

How to Cite

Nguyen, T., Nguyễn Trường Sơn, and Nguyễn Hoàng Việt. “Proposed Deep Neural Network ARTRNet for Automatic Target Recognition for FMCW Radar”. Journal of Military Science and Technology, no. 84, Dec. 2022, pp. 24-31, doi:10.54939/1859-1043.j.mst.84.2022.24-31.

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