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Adaptive Detector of Spare Range-spread Target Based on AR Model

Received: 25 June 2018     Published: 26 June 2018
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Abstract

The detecting of spare range-spread target is discussed in this paper based on the AR model of clutter. Compound-Gaussian clutter is modeled as the AR model, and a regressive approximate generalized likelihood ratio test detector based on scatter number (SN-RAGLRT-CG) is proposed. The probability false alarm of the detector is deduced. It does not need secondary range cells to estimating the parameters of clutter. The simulation results also show that the SN-RAGLRT-CG makes full use of the information scatterers and it improves the detection performance for spare scatterer targets of the detector.

Published in Science Discovery (Volume 6, Issue 3)
DOI 10.11648/j.sd.20180603.19
Page(s) 193-198
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Compound-Gaussian Clutter, Spherically Invariant Random Vector, AR-Model, Generalized Likelihood Ratio Test

References
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[4] He Y, Jian T, Su F, et al. Novel range-spread target detec-tors in non-Gaussian clutter [J]. IEEETransactions on Aerospace and Electronic Systems,2010, 46: 1312-1328.
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[6] CONTE E, LOPS M, RICCI G. Adaptive detection schemes in compound-Gaussian clutter [J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(4): 1058-1069.
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Cite This Article
  • APA Style

    Gu Xinfeng, Xu Zhengfeng, Yan Shuqiang, Hao Xiaolin. (2018). Adaptive Detector of Spare Range-spread Target Based on AR Model. Science Discovery, 6(3), 193-198. https://doi.org/10.11648/j.sd.20180603.19

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    ACS Style

    Gu Xinfeng; Xu Zhengfeng; Yan Shuqiang; Hao Xiaolin. Adaptive Detector of Spare Range-spread Target Based on AR Model. Sci. Discov. 2018, 6(3), 193-198. doi: 10.11648/j.sd.20180603.19

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    AMA Style

    Gu Xinfeng, Xu Zhengfeng, Yan Shuqiang, Hao Xiaolin. Adaptive Detector of Spare Range-spread Target Based on AR Model. Sci Discov. 2018;6(3):193-198. doi: 10.11648/j.sd.20180603.19

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  • @article{10.11648/j.sd.20180603.19,
      author = {Gu Xinfeng and Xu Zhengfeng and Yan Shuqiang and Hao Xiaolin},
      title = {Adaptive Detector of Spare Range-spread Target Based on AR Model},
      journal = {Science Discovery},
      volume = {6},
      number = {3},
      pages = {193-198},
      doi = {10.11648/j.sd.20180603.19},
      url = {https://doi.org/10.11648/j.sd.20180603.19},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20180603.19},
      abstract = {The detecting of spare range-spread target is discussed in this paper based on the AR model of clutter. Compound-Gaussian clutter is modeled as the AR model, and a regressive approximate generalized likelihood ratio test detector based on scatter number (SN-RAGLRT-CG) is proposed. The probability false alarm of the detector is deduced. It does not need secondary range cells to estimating the parameters of clutter. The simulation results also show that the SN-RAGLRT-CG makes full use of the information scatterers and it improves the detection performance for spare scatterer targets of the detector.},
     year = {2018}
    }
    

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  • TY  - JOUR
    T1  - Adaptive Detector of Spare Range-spread Target Based on AR Model
    AU  - Gu Xinfeng
    AU  - Xu Zhengfeng
    AU  - Yan Shuqiang
    AU  - Hao Xiaolin
    Y1  - 2018/06/26
    PY  - 2018
    N1  - https://doi.org/10.11648/j.sd.20180603.19
    DO  - 10.11648/j.sd.20180603.19
    T2  - Science Discovery
    JF  - Science Discovery
    JO  - Science Discovery
    SP  - 193
    EP  - 198
    PB  - Science Publishing Group
    SN  - 2331-0650
    UR  - https://doi.org/10.11648/j.sd.20180603.19
    AB  - The detecting of spare range-spread target is discussed in this paper based on the AR model of clutter. Compound-Gaussian clutter is modeled as the AR model, and a regressive approximate generalized likelihood ratio test detector based on scatter number (SN-RAGLRT-CG) is proposed. The probability false alarm of the detector is deduced. It does not need secondary range cells to estimating the parameters of clutter. The simulation results also show that the SN-RAGLRT-CG makes full use of the information scatterers and it improves the detection performance for spare scatterer targets of the detector.
    VL  - 6
    IS  - 3
    ER  - 

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Author Information
  • China Satellite Maritime Tracking & Control Department, Jiangyin, China

  • China Satellite Maritime Tracking & Control Department, Jiangyin, China

  • China Satellite Maritime Tracking & Control Department, Jiangyin, China

  • Yantai Electricity and Economy Technical Institute, Yantai, China

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