Adaptive Detection of Rician Targets
We address the problem of detecting a signal of interest in Gaussian noise with an unknown covariance matrix, when the amplitude of the signal fluctuates along the observations and follows a Rice distribution. This is typical of a target that consists of one large dominant scatterer and a collection...
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| Veröffentlicht in: | IEEE transactions on aerospace and electronic systems 2023-08, Vol.59 (4), p.4700-4708 |
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| creator | Besson, Olivier |
| description | We address the problem of detecting a signal of interest in Gaussian noise with an unknown covariance matrix, when the amplitude of the signal fluctuates along the observations and follows a Rice distribution. This is typical of a target that consists of one large dominant scatterer and a collection of small independent scatterers. We formulate it as a composite hypothesis testing problem, for which we derive the generalized likelihood ratio test, and show that it ensures a constant false alarm rate. Numerical simulations enable to assess its performance for Rician as well as Swerling I and III targets. It is shown that the new detector incurs no loss for Swerling targets but can offer a significant improvement for Rician targets, especially when the number of training samples is small. |
| doi_str_mv | 10.1109/TAES.2023.3234454 |
| format | Article |
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This is typical of a target that consists of one large dominant scatterer and a collection of small independent scatterers. We formulate it as a composite hypothesis testing problem, for which we derive the generalized likelihood ratio test, and show that it ensures a constant false alarm rate. Numerical simulations enable to assess its performance for Rician as well as Swerling I and III targets. It is shown that the new detector incurs no loss for Swerling targets but can offer a significant improvement for Rician targets, especially when the number of training samples is small.</description><identifier>ISSN: 0018-9251</identifier><identifier>EISSN: 1557-9603</identifier><identifier>DOI: 10.1109/TAES.2023.3234454</identifier><identifier>CODEN: IEARAX</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptive radar detection ; Constant false alarm rate ; constant false alarm rate (CFAR) ; Covariance matrices ; Covariance matrix ; Detectors ; Engineering Sciences ; generalized likelihood ratio test (GLRT) ; Likelihood ratio ; Logic gates ; Radar cross-sections ; Radar detection ; Random noise ; Rician channels ; Rician targets ; Signal and Image processing ; Target detection ; Training</subject><ispartof>IEEE transactions on aerospace and electronic systems, 2023-08, Vol.59 (4), p.4700-4708</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c328t-68509f5c15c407f50f119bb225034d5885985483898f44897b73e060e3b12dab3</citedby><cites>FETCH-LOGICAL-c328t-68509f5c15c407f50f119bb225034d5885985483898f44897b73e060e3b12dab3</cites><orcidid>0000-0001-6079-8446</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10007701$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,780,784,796,885,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10007701$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://hal.science/hal-04283767$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Besson, Olivier</creatorcontrib><title>Adaptive Detection of Rician Targets</title><title>IEEE transactions on aerospace and electronic systems</title><addtitle>T-AES</addtitle><description>We address the problem of detecting a signal of interest in Gaussian noise with an unknown covariance matrix, when the amplitude of the signal fluctuates along the observations and follows a Rice distribution. 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| ispartof | IEEE transactions on aerospace and electronic systems, 2023-08, Vol.59 (4), p.4700-4708 |
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| subjects | Adaptive radar detection Constant false alarm rate constant false alarm rate (CFAR) Covariance matrices Covariance matrix Detectors Engineering Sciences generalized likelihood ratio test (GLRT) Likelihood ratio Logic gates Radar cross-sections Radar detection Random noise Rician channels Rician targets Signal and Image processing Target detection Training |
| title | Adaptive Detection of Rician Targets |
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