Maximum likelihood identification of glint noise

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DC Field	Value	Language
dc.contributor.author	Wu, WR	en_US
dc.date.accessioned	2014-12-08T15:02:56Z	-
dc.date.available	2014-12-08T15:02:56Z	-
dc.date.issued	1996-01-01	en_US
dc.identifier.issn	0018-9251	en_US
dc.identifier.uri	http://dx.doi.org/10.1109/7.481248	en_US
dc.identifier.uri	http://hdl.handle.net/11536/1535	-
dc.description.abstract	If the non-Gaussian distribution function of radar glint noise is known, the Masreliez filter can be applied to improve target tracking performance. We investigate the glint identification problem using the maximum likelihood (ML) method. Two models for the glint distribution are used, a mixture of two Gaussian distributions and a mixture of a Gaussian and a Laplacian distribution An efficient initial estimate method based on the QQ-plot is also proposed. Simulations show that the ML estimates converge to truths.	en_US
dc.language.iso	en_US	en_US
dc.title	Maximum likelihood identification of glint noise	en_US
dc.type	Article	en_US
dc.identifier.doi	10.1109/7.481248	en_US
dc.identifier.journal	IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS	en_US
dc.citation.volume	32	en_US
dc.citation.issue	1	en_US
dc.citation.spage	41	en_US
dc.citation.epage	51	en_US
dc.contributor.department	交大名義發表	zh_TW
dc.contributor.department	電信工程研究所	zh_TW
dc.contributor.department	National Chiao Tung University	en_US
dc.contributor.department	Institute of Communications Engineering	en_US
dc.identifier.wosnumber	WOS:A1996TQ35200005	-
dc.citation.woscount	9	-
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