<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
		<Article>
		<Journal>
			<PublisherName>Majlesi Journal of Electrical Engineering</PublisherName>
			<JournalTitle>Pseudo-Optimum CFAR Detectors in non-Gaussian Clutter</JournalTitle>
			<Issn></Issn>
			<Volume>Volume 1 (2007)</Volume>
			<Issue>Issue 2, September 2007</Issue>
			<PubDate PubStatus="epublish">
                <Year>2024</Year>
                <Month>02</Month>
                <Day>28</Day>
			</PubDate>
		</Journal>
		<ArticleTitle>Pseudo-Optimum CFAR Detectors in non-Gaussian Clutter</ArticleTitle>
		<VernacularTitle></VernacularTitle>
		<FirstPage></FirstPage>
		<LastPage></LastPage>
		<ELocationID EIdType="doi">10.1234/mjee.v1i2.22</ELocationID>
		<Language>EN</Language>
		<AuthorList>
            		</AuthorList>
		<PublicationType>Journal Article</PublicationType>
		<History>
			<PubDate PubStatus="received">
				<Year>2024</Year>
				<Month>02</Month>
				<Day>28</Day>
			</PubDate>
		</History>
		<Abstract>In this paper, the problem of signal detection based on suboptimum-constant false alarm rate (CFAR) detector, in the presence of a mixture of K-distributed clutter, is studied. In this case, a new suboptimum detector named generalized likelihood ratio test and maximum a posteriori (GLRT-MAP) is proposed and compared with generalized likelihood ratio test and linear quadratic (GLRT-LQ) suboptimum detector. The CFAR properties of the GLRT-MAP detector are investigated and compared with that of the GLRT-LQ detector. The simulation results show that the GLRT-MAP is a completely CFAR detector regardless of the clutter distribution and correlation in covariance matrix, whereas the GLRT-LQ is only CFAR detector regardless to clutter distribution. The performance analyses of the GLRT-MAP and GLRT-LQ are investigated by means of Monte Carlo simulation, and results are provided in results section.</Abstract>
		<ObjectList>
            			<Object Type="keyword">
				<Param Name="value">Detection</Param>
			</Object>
						<Object Type="keyword">
				<Param Name="value">GLRT-LQ</Param>
			</Object>
						<Object Type="keyword">
				<Param Name="value">Glrt-MAP</Param>
			</Object>
						<Object Type="keyword">
				<Param Name="value">CFAR. Pseudo-Optimum</Param>
			</Object>
						<Object Type="keyword">
				<Param Name="value">non-Gaussian Clutter</Param>
			</Object>
					</ObjectList>
	</Article>
	</ArticleSet>
