Detection in correlated impulsive noise using fourth-order cumulants
We consider detection and estimation in correlated impulsive noise. The non-Gaussian impulsive noise is modeled as the sum of two linear processes: a nominal part and an impulsive part. This model admits correlated impulsive bursts lasting many data samples. Identifiability of the noise model is est...
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| Veröffentlicht in: | IEEE transactions on signal processing 1996-11, Vol.44 (11), p.2793-2800 |
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| container_title | IEEE transactions on signal processing |
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| creator | Sadler, B.M. |
| description | We consider detection and estimation in correlated impulsive noise. The non-Gaussian impulsive noise is modeled as the sum of two linear processes: a nominal part and an impulsive part. This model admits correlated impulsive bursts lasting many data samples. Identifiability of the noise model is established using fourth- and second-order cumulants. Under this model, the correlated time series can be whitened and an appropriate memoryless nonlinearity applied to attenuate the impulsive events. A detection statistic is then formed from the output of the nonlinearity. In the threshold detection case, the use of cumulants allows identification of the noise in the presence of the signal to be detected, obviating the need for noise-only training records. Simulation results with a sample size of 512 show small loss in detector performance versus an ideal detector with no impulsive part present. |
| doi_str_mv | 10.1109/78.542437 |
| format | Article |
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The non-Gaussian impulsive noise is modeled as the sum of two linear processes: a nominal part and an impulsive part. This model admits correlated impulsive bursts lasting many data samples. Identifiability of the noise model is established using fourth- and second-order cumulants. Under this model, the correlated time series can be whitened and an appropriate memoryless nonlinearity applied to attenuate the impulsive events. A detection statistic is then formed from the output of the nonlinearity. In the threshold detection case, the use of cumulants allows identification of the noise in the presence of the signal to be detected, obviating the need for noise-only training records. Simulation results with a sample size of 512 show small loss in detector performance versus an ideal detector with no impulsive part present.</description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/78.542437</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Applied sciences ; Background noise ; Detection, estimation, filtering, equalization, prediction ; Detectors ; Electromagnetic interference ; Exact sciences and technology ; Filtering ; Gaussian noise ; Information, signal and communications theory ; Radar detection ; Signal and communications theory ; Signal detection ; Signal processing ; Signal, noise ; Sonar detection ; Statistics ; Telecommunications and information theory</subject><ispartof>IEEE transactions on signal processing, 1996-11, Vol.44 (11), p.2793-2800</ispartof><rights>1997 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c337t-b35ba94eb0d0daa86bb5139b360a81e241db6c535cecf3da56d414cc03b071723</citedby><cites>FETCH-LOGICAL-c337t-b35ba94eb0d0daa86bb5139b360a81e241db6c535cecf3da56d414cc03b071723</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/542437$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/542437$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=2495822$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Sadler, B.M.</creatorcontrib><title>Detection in correlated impulsive noise using fourth-order cumulants</title><title>IEEE transactions on signal processing</title><addtitle>TSP</addtitle><description>We consider detection and estimation in correlated impulsive noise. The non-Gaussian impulsive noise is modeled as the sum of two linear processes: a nominal part and an impulsive part. This model admits correlated impulsive bursts lasting many data samples. Identifiability of the noise model is established using fourth- and second-order cumulants. Under this model, the correlated time series can be whitened and an appropriate memoryless nonlinearity applied to attenuate the impulsive events. A detection statistic is then formed from the output of the nonlinearity. In the threshold detection case, the use of cumulants allows identification of the noise in the presence of the signal to be detected, obviating the need for noise-only training records. Simulation results with a sample size of 512 show small loss in detector performance versus an ideal detector with no impulsive part present.</description><subject>Applied sciences</subject><subject>Background noise</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Detectors</subject><subject>Electromagnetic interference</subject><subject>Exact sciences and technology</subject><subject>Filtering</subject><subject>Gaussian noise</subject><subject>Information, signal and communications theory</subject><subject>Radar detection</subject><subject>Signal and communications theory</subject><subject>Signal detection</subject><subject>Signal processing</subject><subject>Signal, noise</subject><subject>Sonar detection</subject><subject>Statistics</subject><subject>Telecommunications and information theory</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1996</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LxDAQhoMouK4evHrqQQQPXZPm-yi7fsGCFwVvJUmnGmmbNWmF_fd26bJXTzMwzzy8vAhdErwgBOs7qRacFYzKIzQjmpEcMymOxx1zmnMlP07RWUrfGBPGtJih1Qp6cL0PXea7zIUYoTE9VJlvN0OT_C9kXfAJsiH57jOrwxD7rzzECmLmhnZoTNenc3RSmybBxX7O0fvjw9vyOV-_Pr0s79e5o1T2uaXcGs3A4gpXxihhLSdUWyqwUQQKRiorHKfcgatpZbioGGHOYWqxJLKgc3QzeTcx_AyQ-rL1yUEzhoAwpLJQhVRKs_9BQSilQo7g7QS6GFKKUJeb6FsTtyXB5a7QUqpyKnRkr_dSk5xp6mg659PhoWCaq2IX8mrCPAAcrnvHH60JfZw</recordid><startdate>19961101</startdate><enddate>19961101</enddate><creator>Sadler, B.M.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><scope>7SC</scope><scope>JQ2</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>19961101</creationdate><title>Detection in correlated impulsive noise using fourth-order cumulants</title><author>Sadler, B.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c337t-b35ba94eb0d0daa86bb5139b360a81e241db6c535cecf3da56d414cc03b071723</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1996</creationdate><topic>Applied sciences</topic><topic>Background noise</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Detectors</topic><topic>Electromagnetic interference</topic><topic>Exact sciences and technology</topic><topic>Filtering</topic><topic>Gaussian noise</topic><topic>Information, signal and communications theory</topic><topic>Radar detection</topic><topic>Signal and communications theory</topic><topic>Signal detection</topic><topic>Signal processing</topic><topic>Signal, noise</topic><topic>Sonar detection</topic><topic>Statistics</topic><topic>Telecommunications and information theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sadler, B.M.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Sadler, B.M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detection in correlated impulsive noise using fourth-order cumulants</atitle><jtitle>IEEE transactions on signal processing</jtitle><stitle>TSP</stitle><date>1996-11-01</date><risdate>1996</risdate><volume>44</volume><issue>11</issue><spage>2793</spage><epage>2800</epage><pages>2793-2800</pages><issn>1053-587X</issn><eissn>1941-0476</eissn><coden>ITPRED</coden><abstract>We consider detection and estimation in correlated impulsive noise. The non-Gaussian impulsive noise is modeled as the sum of two linear processes: a nominal part and an impulsive part. This model admits correlated impulsive bursts lasting many data samples. Identifiability of the noise model is established using fourth- and second-order cumulants. Under this model, the correlated time series can be whitened and an appropriate memoryless nonlinearity applied to attenuate the impulsive events. A detection statistic is then formed from the output of the nonlinearity. In the threshold detection case, the use of cumulants allows identification of the noise in the presence of the signal to be detected, obviating the need for noise-only training records. Simulation results with a sample size of 512 show small loss in detector performance versus an ideal detector with no impulsive part present.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/78.542437</doi><tpages>8</tpages></addata></record> |
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| ispartof | IEEE transactions on signal processing, 1996-11, Vol.44 (11), p.2793-2800 |
| issn | 1053-587X 1941-0476 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Applied sciences Background noise Detection, estimation, filtering, equalization, prediction Detectors Electromagnetic interference Exact sciences and technology Filtering Gaussian noise Information, signal and communications theory Radar detection Signal and communications theory Signal detection Signal processing Signal, noise Sonar detection Statistics Telecommunications and information theory |
| title | Detection in correlated impulsive noise using fourth-order cumulants |
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