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Article: A robust past algorithm for subspace tracking in impulsive noise

TitleA robust past algorithm for subspace tracking in impulsive noise
Authors
KeywordsDOA estimation
Impulsive noise
PAST algorithm
Robust statistics
Subspace tracking
Issue Date2006
PublisherIEEE.
Citation
Ieee Transactions On Signal Processing, 2006, v. 54 n. 1, p. 105-116 How to Cite?
AbstractThe PAST algorithm is an effective and low complexity method for adaptive subspace tracking. However, due to the use of the recursive least squares (RLS) algorithm in estimating the conventional correlation matrix, like other RLS algorithms, it is very sensitive to impulsive noise and the performance can be degraded substantially. To overcome this problem, a new robust correlation matrix estimate, based on robust statistics concept, is proposed in this paper. It is derived from the maximum-likelihood (ML) estimate of a multivariate Gaussian process in contaminated Gaussian noise (CG) similar to the M-estimates in robust statistics. This new estimator is incorporated into the PAST algorithm for robust subspace tracking in impulsive noise. Furthermore, a new restoring mechanism is proposed to combat the hostile effect of long burst of impulses, which sporadically occur in communications systems. The convergence of this new algorithm is analyzed by extending a previous ordinary differential equation (ODE)-based method for PAST. Both theoretical and simulation results show that the proposed algorithm offers improved robustness against impulsive noise over the PAST algorithm. The performance of the new algorithm in nominal Gaussian noise is very close to that of the PAST algorithm. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/45010
ISSN
2015 Impact Factor: 2.624
2015 SCImago Journal Rankings: 2.004
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChan, SCen_HK
dc.contributor.authorWen, Yen_HK
dc.contributor.authorHo, KLen_HK
dc.date.accessioned2007-10-30T06:15:33Z-
dc.date.available2007-10-30T06:15:33Z-
dc.date.issued2006en_HK
dc.identifier.citationIeee Transactions On Signal Processing, 2006, v. 54 n. 1, p. 105-116en_HK
dc.identifier.issn1053-587Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/45010-
dc.description.abstractThe PAST algorithm is an effective and low complexity method for adaptive subspace tracking. However, due to the use of the recursive least squares (RLS) algorithm in estimating the conventional correlation matrix, like other RLS algorithms, it is very sensitive to impulsive noise and the performance can be degraded substantially. To overcome this problem, a new robust correlation matrix estimate, based on robust statistics concept, is proposed in this paper. It is derived from the maximum-likelihood (ML) estimate of a multivariate Gaussian process in contaminated Gaussian noise (CG) similar to the M-estimates in robust statistics. This new estimator is incorporated into the PAST algorithm for robust subspace tracking in impulsive noise. Furthermore, a new restoring mechanism is proposed to combat the hostile effect of long burst of impulses, which sporadically occur in communications systems. The convergence of this new algorithm is analyzed by extending a previous ordinary differential equation (ODE)-based method for PAST. Both theoretical and simulation results show that the proposed algorithm offers improved robustness against impulsive noise over the PAST algorithm. The performance of the new algorithm in nominal Gaussian noise is very close to that of the PAST algorithm. © 2006 IEEE.en_HK
dc.format.extent640537 bytes-
dc.format.extent229190 bytes-
dc.format.extent19303 bytes-
dc.format.extent12429 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEE Transactions on Signal Processingen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectDOA estimationen_HK
dc.subjectImpulsive noiseen_HK
dc.subjectPAST algorithmen_HK
dc.subjectRobust statisticsen_HK
dc.subjectSubspace trackingen_HK
dc.titleA robust past algorithm for subspace tracking in impulsive noiseen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1053-587X&volume=54&issue=1&spage=105&epage=116&date=2006&atitle=A+robust+past+algorithm+for+subspace+tracking+in+impulsive+noiseen_HK
dc.identifier.emailChan, SC:scchan@eee.hku.hken_HK
dc.identifier.emailHo, KL:klho@eee.hku.hken_HK
dc.identifier.authorityChan, SC=rp00094en_HK
dc.identifier.authorityHo, KL=rp00117en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TSP.2005.861072en_HK
dc.identifier.scopuseid_2-s2.0-30344458496en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-30344458496&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume54en_HK
dc.identifier.issue1en_HK
dc.identifier.spage105en_HK
dc.identifier.epage116en_HK
dc.identifier.isiWOS:000234755600010-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridChan, SC=13310287100en_HK
dc.identifier.scopusauthoridWen, Y=55239414600en_HK
dc.identifier.scopusauthoridHo, KL=7403581592en_HK

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