Interpretation of cumulants for array processing
Cumulants can increase the effective aperture of an array, and they suppress non-Gaussian noise. Our earlier works showed these properties to be true for fourth-order cumulants. Here we show these properties are also true for third-order cumulants. We have done this because it is usually good practi...
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| creator | Dogan, M.C. Mendel, J.M. |
| description | Cumulants can increase the effective aperture of an array, and they suppress non-Gaussian noise. Our earlier works showed these properties to be true for fourth-order cumulants. Here we show these properties are also true for third-order cumulants. We have done this because it is usually good practice to work with as lower an order cumulant as possible, if possible, in order to reduce cumulant estimation errors and to work with shorter data lengths. Our Virtual Cross-Correlation Computer (VC/sup 3/), which lets us compute cross-correlations and autocorrelations for all the sensors in an array, as well as for "virtual" sensors, using cumulants, is applicable to third- and fourth-order cumulants. It leads to increased aperture (much greater for fourth-order cumulants than for third-order cumulants), a virtual ESPRIT algorithm, and non-Gaussian noise suppression.< > |
| doi_str_mv | 10.1109/ACSSC.1993.342333 |
| format | Conference Proceeding |
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Our earlier works showed these properties to be true for fourth-order cumulants. Here we show these properties are also true for third-order cumulants. We have done this because it is usually good practice to work with as lower an order cumulant as possible, if possible, in order to reduce cumulant estimation errors and to work with shorter data lengths. Our Virtual Cross-Correlation Computer (VC/sup 3/), which lets us compute cross-correlations and autocorrelations for all the sensors in an array, as well as for "virtual" sensors, using cumulants, is applicable to third- and fourth-order cumulants. 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Press</publisher><subject>Apertures ; Array signal processing ; Autocorrelation ; Estimation error ; Sensor arrays ; Virtual colonoscopy</subject><ispartof>Proceedings of 27th Asilomar Conference on Signals, Systems and Computers, 1993, p.1260-1264 vol.2</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/342333$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,4036,4037,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/342333$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Dogan, M.C.</creatorcontrib><creatorcontrib>Mendel, J.M.</creatorcontrib><title>Interpretation of cumulants for array processing</title><title>Proceedings of 27th Asilomar Conference on Signals, Systems and Computers</title><addtitle>ACSSC</addtitle><description>Cumulants can increase the effective aperture of an array, and they suppress non-Gaussian noise. Our earlier works showed these properties to be true for fourth-order cumulants. Here we show these properties are also true for third-order cumulants. We have done this because it is usually good practice to work with as lower an order cumulant as possible, if possible, in order to reduce cumulant estimation errors and to work with shorter data lengths. Our Virtual Cross-Correlation Computer (VC/sup 3/), which lets us compute cross-correlations and autocorrelations for all the sensors in an array, as well as for "virtual" sensors, using cumulants, is applicable to third- and fourth-order cumulants. It leads to increased aperture (much greater for fourth-order cumulants than for third-order cumulants), a virtual ESPRIT algorithm, and non-Gaussian noise suppression.< ></description><subject>Apertures</subject><subject>Array signal processing</subject><subject>Autocorrelation</subject><subject>Estimation error</subject><subject>Sensor arrays</subject><subject>Virtual colonoscopy</subject><issn>1058-6393</issn><issn>2576-2303</issn><isbn>0818641207</isbn><isbn>9780818641206</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1993</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj8lqwzAUAEUXqJvmA9qTf8Due3qylmMwXQKBHJKegyTLRSWxjeQc8vctpHOZ28Aw9oxQI4J5XbW7XVujMVST4ER0wwreKFlxArplj6BRS4Ec1B0rEBpdSTL0wJY5_8AfokENTcFgPcwhTSnMdo7jUI596c-n89EOcy77MZU2JXsppzT6kHMcvp_YfW-POSz_vWBf72_79rPabD_W7WpTRVR8roQhG8Bxz7V0plPaCVDSB0CpBYBXpLVyFgM3opONsOCclNzpznSOS08L9nLtxhDCYUrxZNPlcH2lX4t9RWU</recordid><startdate>1993</startdate><enddate>1993</enddate><creator>Dogan, M.C.</creator><creator>Mendel, J.M.</creator><general>IEEE Comput. Soc. Press</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1993</creationdate><title>Interpretation of cumulants for array processing</title><author>Dogan, M.C. ; Mendel, J.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i172t-493ae0b2c286b9d78b4076ce0168400c73887ba1e294d654a0bb662b8d9db26c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1993</creationdate><topic>Apertures</topic><topic>Array signal processing</topic><topic>Autocorrelation</topic><topic>Estimation error</topic><topic>Sensor arrays</topic><topic>Virtual colonoscopy</topic><toplevel>online_resources</toplevel><creatorcontrib>Dogan, M.C.</creatorcontrib><creatorcontrib>Mendel, J.M.</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/IET Electronic Library</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>Dogan, M.C.</au><au>Mendel, J.M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Interpretation of cumulants for array processing</atitle><btitle>Proceedings of 27th Asilomar Conference on Signals, Systems and Computers</btitle><stitle>ACSSC</stitle><date>1993</date><risdate>1993</risdate><spage>1260</spage><epage>1264 vol.2</epage><pages>1260-1264 vol.2</pages><issn>1058-6393</issn><eissn>2576-2303</eissn><isbn>0818641207</isbn><isbn>9780818641206</isbn><abstract>Cumulants can increase the effective aperture of an array, and they suppress non-Gaussian noise. Our earlier works showed these properties to be true for fourth-order cumulants. Here we show these properties are also true for third-order cumulants. We have done this because it is usually good practice to work with as lower an order cumulant as possible, if possible, in order to reduce cumulant estimation errors and to work with shorter data lengths. Our Virtual Cross-Correlation Computer (VC/sup 3/), which lets us compute cross-correlations and autocorrelations for all the sensors in an array, as well as for "virtual" sensors, using cumulants, is applicable to third- and fourth-order cumulants. It leads to increased aperture (much greater for fourth-order cumulants than for third-order cumulants), a virtual ESPRIT algorithm, and non-Gaussian noise suppression.< ></abstract><pub>IEEE Comput. Soc. Press</pub><doi>10.1109/ACSSC.1993.342333</doi></addata></record> |
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| ispartof | Proceedings of 27th Asilomar Conference on Signals, Systems and Computers, 1993, p.1260-1264 vol.2 |
| issn | 1058-6393 2576-2303 |
| language | eng |
| recordid | cdi_ieee_primary_342333 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Apertures Array signal processing Autocorrelation Estimation error Sensor arrays Virtual colonoscopy |
| title | Interpretation of cumulants for array processing |
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