Unresolved Rayleigh target detection using monopulse measurements
When the returns from two or more targets interfere (i.e., the signals are not resolved in the frequency or time domains) in a monopulse radar system, the direction-of-arrival (DOA) estimate indicated by the monopulse ratio can wander far beyond the angular separation of the targets. Generalized max...
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| Veröffentlicht in: | IEEE transactions on aerospace and electronic systems 1998-04, Vol.34 (2), p.543-552 |
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| container_title | IEEE transactions on aerospace and electronic systems |
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| creator | Blair, W.D. Brandt-Pearce, M. |
| description | When the returns from two or more targets interfere (i.e., the signals are not resolved in the frequency or time domains) in a monopulse radar system, the direction-of-arrival (DOA) estimate indicated by the monopulse ratio can wander far beyond the angular separation of the targets. Generalized maximum likelihood (GML) detection of the presence of unresolved Rayleigh targets is developed with probability density functions (pdfs) conditioned on the measured amplitude of the target echoes. The Neyman-Pearson detection algorithm uses both the in-phase and quadrature portions of the monopulse ratio and requires no a priori knowledge of the signal-to-noise ratio (SNR) or DOA of either target. Receiver operating characteristic (ROC) curves are given along with simulation results that illustrate the performance and application of the algorithm. |
| doi_str_mv | 10.1109/7.670335 |
| format | Article |
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Generalized maximum likelihood (GML) detection of the presence of unresolved Rayleigh targets is developed with probability density functions (pdfs) conditioned on the measured amplitude of the target echoes. The Neyman-Pearson detection algorithm uses both the in-phase and quadrature portions of the monopulse ratio and requires no a priori knowledge of the signal-to-noise ratio (SNR) or DOA of either target. 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Generalized maximum likelihood (GML) detection of the presence of unresolved Rayleigh targets is developed with probability density functions (pdfs) conditioned on the measured amplitude of the target echoes. The Neyman-Pearson detection algorithm uses both the in-phase and quadrature portions of the monopulse ratio and requires no a priori knowledge of the signal-to-noise ratio (SNR) or DOA of either target. Receiver operating characteristic (ROC) curves are given along with simulation results that illustrate the performance and application of the algorithm.</description><subject>Density measurement</subject><subject>Detection algorithms</subject><subject>Direction of arrival estimation</subject><subject>Frequency estimation</subject><subject>Maximum likelihood detection</subject><subject>Maximum likelihood estimation</subject><subject>Object detection</subject><subject>Probability density function</subject><subject>Radar detection</subject><subject>Signal resolution</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqN0EtLw0AQB_BFFKxV8OwpJ_GSupvNvo6l-IKCIPYc9jFbI0m27iZCv70pKV71MsPM_PgfBqFrgheEYHUvFlxgStkJmhHGRK44pqdohjGRuSoYOUcXKX2OYylLOkPLTRchheYbXPam9w3U24-s13ELfeagB9vXocuGVHfbrA1d2A1NgqwFnYYILXR9ukRnXo_Lq2Ofo83jw_vqOV-_Pr2sluvcUir6XHtRaCKcNsoYcIIJ66x3xjtdWK4Nw8pQzrygIEkpGCdlIT3xlhtiHZR0jm6n3F0MXwOkvmrrZKFpdAdhSFUhlZQK83_Akqux_A05l6RQh8S7CdoYUorgq12sWx33FcHV4euVqKavj_RmojUA_LLj8Qd1v34c</recordid><startdate>19980401</startdate><enddate>19980401</enddate><creator>Blair, W.D.</creator><creator>Brandt-Pearce, M.</creator><general>IEEE</general><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope><scope>7SP</scope><scope>7TB</scope><scope>FR3</scope></search><sort><creationdate>19980401</creationdate><title>Unresolved Rayleigh target detection using monopulse measurements</title><author>Blair, W.D. ; Brandt-Pearce, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c337t-af72a17dab9bbed757cdcfdbfda2c6ab509b365f73e8147561428f1fc6b1cde43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Density measurement</topic><topic>Detection algorithms</topic><topic>Direction of arrival estimation</topic><topic>Frequency estimation</topic><topic>Maximum likelihood detection</topic><topic>Maximum likelihood estimation</topic><topic>Object detection</topic><topic>Probability density function</topic><topic>Radar detection</topic><topic>Signal resolution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Blair, W.D.</creatorcontrib><creatorcontrib>Brandt-Pearce, M.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on aerospace and electronic systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Blair, W.D.</au><au>Brandt-Pearce, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Unresolved Rayleigh target detection using monopulse measurements</atitle><jtitle>IEEE transactions on aerospace and electronic systems</jtitle><stitle>T-AES</stitle><date>1998-04-01</date><risdate>1998</risdate><volume>34</volume><issue>2</issue><spage>543</spage><epage>552</epage><pages>543-552</pages><issn>0018-9251</issn><eissn>1557-9603</eissn><coden>IEARAX</coden><abstract>When the returns from two or more targets interfere (i.e., the signals are not resolved in the frequency or time domains) in a monopulse radar system, the direction-of-arrival (DOA) estimate indicated by the monopulse ratio can wander far beyond the angular separation of the targets. Generalized maximum likelihood (GML) detection of the presence of unresolved Rayleigh targets is developed with probability density functions (pdfs) conditioned on the measured amplitude of the target echoes. The Neyman-Pearson detection algorithm uses both the in-phase and quadrature portions of the monopulse ratio and requires no a priori knowledge of the signal-to-noise ratio (SNR) or DOA of either target. Receiver operating characteristic (ROC) curves are given along with simulation results that illustrate the performance and application of the algorithm.</abstract><pub>IEEE</pub><doi>10.1109/7.670335</doi><tpages>10</tpages></addata></record> |
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| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Density measurement Detection algorithms Direction of arrival estimation Frequency estimation Maximum likelihood detection Maximum likelihood estimation Object detection Probability density function Radar detection Signal resolution |
| title | Unresolved Rayleigh target detection using monopulse measurements |
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