Volume 30 Issue 2
Apr.  2021
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LU Shuping, DING Feng, LI Ranwei, “Robust Centralized CFAR Detection for Multistatic Sonar Systems,” Chinese Journal of Electronics, vol. 30, no. 2, pp. 322-330, 2021, doi: 10.1049/cje.2021.02.003
Citation: LU Shuping, DING Feng, LI Ranwei, “Robust Centralized CFAR Detection for Multistatic Sonar Systems,” Chinese Journal of Electronics, vol. 30, no. 2, pp. 322-330, 2021, doi: 10.1049/cje.2021.02.003

Robust Centralized CFAR Detection for Multistatic Sonar Systems

doi: 10.1049/cje.2021.02.003
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  • Author Bio:

    LU Shuping   was born in Henan Province, China. He received the Ph.D. degree from University of Electronic Science and Technology of China in 2018. His research interests include signal and information processing for multistatic sonar systems. (Email: lukeuestc@163.com)

    DING Feng   was born in Jiangsu Province, China. He is a professor of Hangzhou Applied Acoustic Research Institute. His research interests include sonar system design and underwater acoustic signal processing. (Email: 2960755381@qq.com)

    LI Ranwei   was born in Heilongjiang Province, China. He is a professor of Hangzhou Applied Acoustic Research Institute. His research interests include sonar system design and underwater acoustic signal processing. (Email: lirw501@sina.com)

  • Received Date: 2020-06-02
  • Accepted Date: 2020-11-23
  • Publish Date: 2021-03-01
  • This paper proposes a novel centralized Constant false alarm ratio (CFAR) detector for multistatic sonar systems. The detector employs the idea of Variability index (Ⅵ) CFAR detection, to adaptively select the matched detection algorithm in diversified undersea environments. All the echo data from mutistatic sonar receivers are transmitted into the centralized fusion center. Firstly, the background statistics of reference cells from different nodes are analyzed. Then choose one appropriate centralized detection algorithm according to the background statistics, which refers to the centralized Cell averaging CFAR (CA-CFAR), greatest of CFAR, order statistic CFAR detection algorithms. The performance of the proposed detector is analyzed by computer simulation and measured sonar data. The results show that, compared to the centralized CA-CFAR detector, the introduced centralized detector achieves a better robustness in multiply heterogeneous undersea environments.
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