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Research on Sparse Targets Detection Methods Based on GLRT in Non-Gaussian Clutter
Science Discovery
Volume 5, Issue 1, February 2017, Pages: 25-32
Received: Mar. 29, 2017; Published: Mar. 31, 2017
Volume 5, Issue 1, February 2017, Pages: 25-32
Received: Mar. 29, 2017; Published: Mar. 31, 2017
Views 1528 Downloads 82
Authors
Gu Xinfeng, 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
Huang Kun, China Satellite Maritime Tracking & Control Department, Jiangyin, China
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.
Keywords
Non-Gaussian Clutter, Range-Spread Target, Constant False Alarm Rate, Detection
To cite this article
Gu Xinfeng,
Yan Shuqiang,
Hao Xiaolin,
Huang Kun,
Research on Sparse Targets Detection Methods Based on GLRT in Non-Gaussian Clutter, Science Discovery.
Vol. 5, No. 1,
2017, pp. 25-32.
doi: 10.11648/j.sd.20170501.15
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