For the problem of detecting range-spread target with spare scatterers in non-Gaussian clutter modeled as spherically invariant random vector(SIRV). Firstly, it is assumed that the number of the target scatterers is known and a generalized likelihood ratio test detector based on scatterers number (SN-GLRT) is proposed. Then a sparse scatterers target detector based on GLRT (SST-GLRT) is proposed for unknowing the number of scatterers. The detection statistic of the SSR-GLRT is the weighted sum of the detection statistic of the SN-GLRT. The SSD-SST-GLRT and the NSSD-SST-GLRT are proposed based on the density of the scatterers. The analytical expression relating false alarm probability to detection threshold is deduced and the CFAR property of the SSD-SST-GLRT and the NSSD-SST-GLRT is proved. The results show that the detection performance of NSSD-SST-GLRT is better than the NSDD-GLRT. The detection performance of the SSD-SST-GLRT is better than the SDD-GLRT when the number of scatterers is known. The robustness of the SSD-SST-GLRT is better than the MSDD when the number of scatterers is unknown.
| Published in | Science Discovery (Volume 5, Issue 1) |
| DOI | 10.11648/j.sd.20170501.15 |
| Page(s) | 25-32 |
| 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. |
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Copyright © The Author(s), 2024. Published by Science Publishing Group |
Non-Gaussian Clutter, Range-Spread Target, Constant False Alarm Rate, Detection
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APA Style
Gu Xinfeng, Yan Shuqiang, Hao Xiaolin, Huang Kun. (2017). Research on Sparse Targets Detection Methods Based on GLRT in Non-Gaussian Clutter. Science Discovery, 5(1), 25-32. https://doi.org/10.11648/j.sd.20170501.15
ACS Style
Gu Xinfeng; Yan Shuqiang; Hao Xiaolin; Huang Kun. Research on Sparse Targets Detection Methods Based on GLRT in Non-Gaussian Clutter. Sci. Discov. 2017, 5(1), 25-32. doi: 10.11648/j.sd.20170501.15
AMA Style
Gu Xinfeng, Yan Shuqiang, Hao Xiaolin, Huang Kun. Research on Sparse Targets Detection Methods Based on GLRT in Non-Gaussian Clutter. Sci Discov. 2017;5(1):25-32. doi: 10.11648/j.sd.20170501.15
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Download@article{10.11648/j.sd.20170501.15,
author = {Gu Xinfeng and Yan Shuqiang and Hao Xiaolin and Huang Kun},
title = {Research on Sparse Targets Detection Methods Based on GLRT in Non-Gaussian Clutter},
journal = {Science Discovery},
volume = {5},
number = {1},
pages = {25-32},
doi = {10.11648/j.sd.20170501.15},
url = {https://doi.org/10.11648/j.sd.20170501.15},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20170501.15},
abstract = {For the problem of detecting range-spread target with spare scatterers in non-Gaussian clutter modeled as spherically invariant random vector(SIRV). Firstly, it is assumed that the number of the target scatterers is known and a generalized likelihood ratio test detector based on scatterers number (SN-GLRT) is proposed. Then a sparse scatterers target detector based on GLRT (SST-GLRT) is proposed for unknowing the number of scatterers. The detection statistic of the SSR-GLRT is the weighted sum of the detection statistic of the SN-GLRT. The SSD-SST-GLRT and the NSSD-SST-GLRT are proposed based on the density of the scatterers. The analytical expression relating false alarm probability to detection threshold is deduced and the CFAR property of the SSD-SST-GLRT and the NSSD-SST-GLRT is proved. The results show that the detection performance of NSSD-SST-GLRT is better than the NSDD-GLRT. The detection performance of the SSD-SST-GLRT is better than the SDD-GLRT when the number of scatterers is known. The robustness of the SSD-SST-GLRT is better than the MSDD when the number of scatterers is unknown.},
year = {2017}
}
TY - JOUR T1 - Research on Sparse Targets Detection Methods Based on GLRT in Non-Gaussian Clutter AU - Gu Xinfeng AU - Yan Shuqiang AU - Hao Xiaolin AU - Huang Kun Y1 - 2017/03/31 PY - 2017 N1 - https://doi.org/10.11648/j.sd.20170501.15 DO - 10.11648/j.sd.20170501.15 T2 - Science Discovery JF - Science Discovery JO - Science Discovery SP - 25 EP - 32 PB - Science Publishing Group SN - 2331-0650 UR - https://doi.org/10.11648/j.sd.20170501.15 AB - For the problem of detecting range-spread target with spare scatterers in non-Gaussian clutter modeled as spherically invariant random vector(SIRV). Firstly, it is assumed that the number of the target scatterers is known and a generalized likelihood ratio test detector based on scatterers number (SN-GLRT) is proposed. Then a sparse scatterers target detector based on GLRT (SST-GLRT) is proposed for unknowing the number of scatterers. The detection statistic of the SSR-GLRT is the weighted sum of the detection statistic of the SN-GLRT. The SSD-SST-GLRT and the NSSD-SST-GLRT are proposed based on the density of the scatterers. The analytical expression relating false alarm probability to detection threshold is deduced and the CFAR property of the SSD-SST-GLRT and the NSSD-SST-GLRT is proved. The results show that the detection performance of NSSD-SST-GLRT is better than the NSDD-GLRT. The detection performance of the SSD-SST-GLRT is better than the SDD-GLRT when the number of scatterers is known. The robustness of the SSD-SST-GLRT is better than the MSDD when the number of scatterers is unknown. VL - 5 IS - 1 ER -
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