Bayesian probability theory applied to the problem of radar target discrimination
The task of discriminating among a set of N known targets based on their radar returns is viewed as a problem of information processing, calling for a full application of probability theory. Two distinct problem areas are investigated. First, Bayesian probability theory is used to derive an expressi...
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| creator | Riggs, L.S. Smith, C.R. |
| description | The task of discriminating among a set of N known targets based on their radar returns is viewed as a problem of information processing, calling for a full application of probability theory. Two distinct problem areas are investigated. First, Bayesian probability theory is used to derive an expression for an enhanced discrimination waveform which, in the two-target case, maximizes the log odds in favor of one target over the other. Numerical results are provided which show that best discrimination, in the simple two-target case, occurs when the incident waveform has its energy concentrated near the frequency where the difference in the impulse response of the two targets reaches a maximum. Second, probability theory is used to discriminate among a set of targets based on their high-range-resolution radar returns. Example calculations show that for the four-target case the Bayesian algorithm identifies the unknown target correctly greater than 90% of the time for signal-to-noise ratios as low as 2 (3 dB).< > |
| doi_str_mv | 10.1109/APS.1992.221662 |
| format | Conference Proceeding |
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Example calculations show that for the four-target case the Bayesian algorithm identifies the unknown target correctly greater than 90% of the time for signal-to-noise ratios as low as 2 (3 dB).< ></description><identifier>ISBN: 0780307305</identifier><identifier>ISBN: 9780780307308</identifier><identifier>DOI: 10.1109/APS.1992.221662</identifier><language>eng</language><publisher>IEEE</publisher><subject>Bayesian methods ; Frequency ; Gaussian noise ; Information processing ; Missiles ; Physical optics ; Radar applications ; Radar theory ; Resonance ; Transfer functions</subject><ispartof>IEEE Antennas and Propagation Society International Symposium 1992 Digest, 1992, p.1246-1249 vol.3</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/221662$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,4036,4037,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/221662$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Riggs, L.S.</creatorcontrib><creatorcontrib>Smith, C.R.</creatorcontrib><title>Bayesian probability theory applied to the problem of radar target discrimination</title><title>IEEE Antennas and Propagation Society International Symposium 1992 Digest</title><addtitle>APS</addtitle><description>The task of discriminating among a set of N known targets based on their radar returns is viewed as a problem of information processing, calling for a full application of probability theory. Two distinct problem areas are investigated. First, Bayesian probability theory is used to derive an expression for an enhanced discrimination waveform which, in the two-target case, maximizes the log odds in favor of one target over the other. Numerical results are provided which show that best discrimination, in the simple two-target case, occurs when the incident waveform has its energy concentrated near the frequency where the difference in the impulse response of the two targets reaches a maximum. Second, probability theory is used to discriminate among a set of targets based on their high-range-resolution radar returns. Example calculations show that for the four-target case the Bayesian algorithm identifies the unknown target correctly greater than 90% of the time for signal-to-noise ratios as low as 2 (3 dB).< ></description><subject>Bayesian methods</subject><subject>Frequency</subject><subject>Gaussian noise</subject><subject>Information processing</subject><subject>Missiles</subject><subject>Physical optics</subject><subject>Radar applications</subject><subject>Radar theory</subject><subject>Resonance</subject><subject>Transfer functions</subject><isbn>0780307305</isbn><isbn>9780780307308</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1992</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotT0tLxDAYDIigrnsWPOUPtObRvI7r4gsWVNz78jX5opFuW9Jc-u-trnMZGIZ5EHLDWc05c3ebt4-aOydqIbjW4oxcMWOZZEYydUHW0_TNFihlXGMuyfs9zDgl6OmYhxba1KUy0_KFQ54pjGOXMNAy_Cp_jg6PdIg0Q4BMC-RPLDSkyed0TD2UNPTX5DxCN-H6n1dk__iw3z5Xu9enl-1mVyXrSoVecSO1BjDBCyGVDdiAYc5aDizG1utGQVxWG-ktxtCGBpwWDbaK--DlityeYhMiHsalH_J8OH2WPzDUTl8</recordid><startdate>1992</startdate><enddate>1992</enddate><creator>Riggs, L.S.</creator><creator>Smith, C.R.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1992</creationdate><title>Bayesian probability theory applied to the problem of radar target discrimination</title><author>Riggs, L.S. ; Smith, C.R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i89t-ec517366aa7dc22358de4a709881a0ffbc645af07373c8efdbd4a9624eb51cdc3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1992</creationdate><topic>Bayesian methods</topic><topic>Frequency</topic><topic>Gaussian noise</topic><topic>Information processing</topic><topic>Missiles</topic><topic>Physical optics</topic><topic>Radar applications</topic><topic>Radar theory</topic><topic>Resonance</topic><topic>Transfer functions</topic><toplevel>online_resources</toplevel><creatorcontrib>Riggs, L.S.</creatorcontrib><creatorcontrib>Smith, C.R.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Riggs, L.S.</au><au>Smith, C.R.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Bayesian probability theory applied to the problem of radar target discrimination</atitle><btitle>IEEE Antennas and Propagation Society International Symposium 1992 Digest</btitle><stitle>APS</stitle><date>1992</date><risdate>1992</risdate><spage>1246</spage><epage>1249 vol.3</epage><pages>1246-1249 vol.3</pages><isbn>0780307305</isbn><isbn>9780780307308</isbn><abstract>The task of discriminating among a set of N known targets based on their radar returns is viewed as a problem of information processing, calling for a full application of probability theory. Two distinct problem areas are investigated. First, Bayesian probability theory is used to derive an expression for an enhanced discrimination waveform which, in the two-target case, maximizes the log odds in favor of one target over the other. Numerical results are provided which show that best discrimination, in the simple two-target case, occurs when the incident waveform has its energy concentrated near the frequency where the difference in the impulse response of the two targets reaches a maximum. Second, probability theory is used to discriminate among a set of targets based on their high-range-resolution radar returns. Example calculations show that for the four-target case the Bayesian algorithm identifies the unknown target correctly greater than 90% of the time for signal-to-noise ratios as low as 2 (3 dB).< ></abstract><pub>IEEE</pub><doi>10.1109/APS.1992.221662</doi></addata></record> |
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| identifier | ISBN: 0780307305 |
| ispartof | IEEE Antennas and Propagation Society International Symposium 1992 Digest, 1992, p.1246-1249 vol.3 |
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| language | eng |
| recordid | cdi_ieee_primary_221662 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Bayesian methods Frequency Gaussian noise Information processing Missiles Physical optics Radar applications Radar theory Resonance Transfer functions |
| title | Bayesian probability theory applied to the problem of radar target discrimination |
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