Volume 12 Issue 4
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GAO Xunzhang, ZHANG Zhiwei, LIU Mei, et al. Intelligent radar image recognition countermeasures: A review[J]. Journal of Radars, 2023, 12(4): 696–712. doi: 10.12000/JR23098
Citation: GAO Xunzhang, ZHANG Zhiwei, LIU Mei, et al. Intelligent radar image recognition countermeasures: A review[J]. Journal of Radars, 2023, 12(4): 696–712. doi: 10.12000/JR23098
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Intelligent Radar Image Recognition Countermeasures: A Review

doi: 10.12000/JR23098

  • College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China

Funds:  The National Natural Science Foundation of China (61921001)
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  • Corresponding author: GAO Xunzhang, gaoxunzhang@nudt.edu.cn; ZHANG Zhiwei, 514131141@qq.com
  • Received Date: 2023-05-29
  • Rev Recd Date: 2023-07-13
    • Available Online: 2023-07-17
  • Publish Date: 2023-07-26
    Abstract
  • Intelligent radar image recognition based on Deep Neural Networks (DNN) has become an important topic in radar information processing. However, DNN models are susceptible to adversarial attacks. Malicious attackers can cause intelligent image recognition models to make incorrect predictions, considerably reducing their recognition accuracy and robustness. This article reviews recent research progress on intelligent radar image recognition countermeasures. Then it summarizes the adversarial attack methods on one/two-dimensional radar image recognition models and adversarial defense methods. Finally, it discusses five open questions worthy of in-depth research in intelligent radar image recognition countermeasures.

     

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