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Volume 29 Issue 5
 
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Article Navigation >  Journal of Unmanned Undersea Systems  > 2021  >  29(5): 533-540
SONG Qiong, YAN Sheng, HAO Cheng-peng, HOU Chao-huan. Robust Adaptive Detection Algorithm of Underwater Targets under Range Cell Migration[J]. Journal of Unmanned Undersea Systems, 2021, 29(5): 533-540. doi: 10.11993/j.issn.2096-3920.2021.05.004
Citation: SONG Qiong, YAN Sheng, HAO Cheng-peng, HOU Chao-huan. Robust Adaptive Detection Algorithm of Underwater Targets under Range Cell Migration[J]. Journal of Unmanned Undersea Systems, 2021, 29(5): 533-540. doi: 10.11993/j.issn.2096-3920.2021.05.004
shu

Robust Adaptive Detection Algorithm of Underwater Targets under Range Cell Migration

doi: 10.11993/j.issn.2096-3920.2021.05.004
  • 1.

    The Institute of Acoustics of the Chinese Academy of Sciences, Beijing 100190, China

  • 2.

    School of Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

  • Received Date: 2021-02-08
  • Rev Recd Date: 2021-03-09
  • Publish Date: 2021-10-31
    Abstract
  • The performance of target adaptive detectors decreases owing to range cell migration(RCM), which is caused by a target moving at high speed. When the detection occurs underwater, this environment also results in a lack of auxiliary data. To solve this problem, this study presents a new adaptive detection algorithm. First, the sonar echo is modeled as multiple time-domain sequences based on the model order selection theory. Then, the multiple hypothesis testing model of the target under RCM is improved by using the persymmetric structure of the covariance matrix of the symmetric array. Finally, a new detection algorithm based on the persymmetric generalized information criterion adaptive matched filter(PM-AMF) is developed. Simulation results show that the PM-AMF detection algorithm reduces the dependence on auxiliary data and accurately estimates the position of the target echo under RCM, achieving a good performance on target detection

     

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