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

Gu Xinfeng; Xu Zhengfeng; Yan Shuqiang; Hao Xiaolin

doi:doi:10.11648/j.sd.20180603.19

| Peer-Reviewed

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

Gu Xinfeng, Xu Zhengfeng, Yan Shuqiang, Hao Xiaolin

Published in Science Discovery (Volume 6, Issue 3)

Received: 25 June 2018 Published: 26 June 2018

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

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

[1]	Robey F C, Fuhrmann D R, Kelly E J, etc. A CFAR adaptive matched filter detector[J]. IEEE Transactions on Aerospace and Electronic Systems, 1992, 28 (1): 208-216.
[2]	何友,关键,孟祥伟,等.雷达目标检测与恒虚警处理(第二版)[M].北京,清华大学出版社,2011。
[3]	简涛,何友,苏峰,等.高距离分辨率雷达目标检测研究现状与进展[J].宇航学报,2010,31(12):2623-2628。
[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.
[5]	简涛,何友,苏峰,等.SIRV杂波下距离扩展目标CFAR检测器[J].电子学报,2010,38(12):2740-2744。
[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.
[7]	Gerlach K. Spatially distributed target detection in non-Gaussian clutter [J]. IEEE Transactions on Aerospace and Electronic Systems, 1999, 35(3):926-934.
[8]	Gu Xinfeng, Hao Xiaolin, Liu Tongling. Range-Spread Target Adaptive Detector for Non-Gaussian Clutter[J]. Science Discovery, 2017, 5(1):48-52.
[9]	Melvin, W.L., Space-time adaptive radar performance in heterogeneous clutter. IEEE Transactions on Aerospace and Electronic Systems, 2000. 36(2): 621-633.
[10]	McDonald K F, Blum R S. Performance characterization of space-time adaptive processing algorithms for distributed target detection in non-ideal environments[C]. Proceedings of the IEEE Radar Conference, 2002: 298-303.
[11]	Alfano G, De Maio A, Farina A. Model-based adaptive detection of range-spread targets[J]. IEE Proceedings Pt. F Radar, Sonar and Navigation, 2004, 151(1): 2-10.
[12]	Sheikhi A, Nayebi M M, Aref M R. Adaptive detection algorithm for radar signal in autoregressive interference[J]. IEE Proc.-Radar Sonar Navig., 1998, 145 (5): 309-314.
[13]	Haykin, S. and A. Steinhardt, Adaptive radar detection and estimation1992, New York: Wiley.
[14]	Gini, F. and M. Greco, Covariance matrix estimation for CFAR detection in correlated heavy tailed clutter. Signal Processing, 2002. 82(12): 1847-1859.

Cite This Article

Plain Text BibTeX RIS

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

Copy | Download

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

Copy | Download

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

Copy | Download

@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}
}

Copy | Download

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  -

Copy | Download

Author Information

Gu Xinfeng

China Satellite Maritime Tracking & Control Department, Jiangyin, China
Xu Zhengfeng

China Satellite Maritime Tracking & Control Department, Jiangyin, China
Yan Shuqiang

China Satellite Maritime Tracking & Control Department, Jiangyin, China
Hao Xiaolin

Yantai Electricity and Economy Technical Institute, Yantai, China

Download PDF

Sections

Plain Text BibTeX RIS

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

Copy | Download

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

Copy | Download

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

Copy | Download

@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}
}

Copy | Download

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  -

Copy | Download