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QUAN Yinghui, WU Yaojun, DUAN Lining, et al. A review of radar signal processing based on sparse recovery[J]. Journal of Radars, 2024, 13(1): 46–67. doi: 10.12000/JR23211
Citation: QUAN Yinghui, WU Yaojun, DUAN Lining, et al. A review of radar signal processing based on sparse recovery[J]. Journal of Radars, 2024, 13(1): 46–67. doi: 10.12000/JR23211
shu

A Review of Radar Signal Processing Based on Sparse Recovery

DOI: 10.12000/JR23211
  • 1.

    School of Electronic Engineering, Xidian University, Xi’an 710071, China

  • 2.

    Xi’an Key Laboratory of Advanced Remote Sensing, Xi’an 710071, China

  • 3.

    State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China

  • 4.

    Academy of Advanced Interdisciplinary Research, Xidian University, Xi’an 710071, China

Funds:  The National Natural Science Foundation of China (62331019), The Shaanxi Provincial Science Fund for Distinguished Young Scholars (2021JC-23), The Science and Technology Innovation Team of Shaanxi Province (2019TD-002)
More Information
  • Corresponding author: QUAN Yinghui, yhquan@mail.xidian.edu.cn
  • Received Date: 2023-11-02
  • Rev Recd Date: 2024-01-06
    • Available Online: 2024-01-08
  • Publish Date: 2024-01-11
    Abstract
  • With the growing demand for radar target detection, Sparse Recovery (SR) technology based on the Compressive Sensing (CS) model has been widely used in radar signal processing. This paper first outlines the fundamental theory of SR and then introduces the sparse characteristics in radar signal processing from the perspectives of scene sparsity and observation sparsity. Subsequently, it explores these sparse properties to provide an overview of CS applications in radar signal processing, including spatial domain processing, pulse compression, coherent processing, radar imaging, and target detection. Finally, the paper summarizes the applications of CS in radar signal processing.

     

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