File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: A new robust Kalman filter-based subspace tracking algorithm in an impulsive noise environment

TitleA new robust Kalman filter-based subspace tracking algorithm in an impulsive noise environment
Authors
KeywordsImpulsive noise
Kalman filter
Kalman filter with variable number of measurements (KFVNM)
least squares
projection approximation subspace tracking (PAST)
Issue Date2010
PublisherIEEE.
Citation
Ieee Transactions On Circuits And Systems Ii: Express Briefs, 2010, v. 57 n. 9, p. 740-744 How to Cite?
AbstractThe conventional projection approximation subspace tracking (PAST) algorithm is based on the recursive least-squares algorithm, and its performance will degrade considerably when the subspace rapidly changes and the additive noise is impulsive. This brief proposes a new robust Kalman filter-based subspace tracking algorithm to overcome these two limitations of the PAST algorithm. It is based on a new extension of the adaptive Kalman filter with variable number of measurements (KFVNM) for tracking fast-varying subspace. Furthermore, M-estimation is incorporated into this KFVNM algorithm to combat the adverse effects of impulsive noise. Simulation results show that the robust KFVNM-based subspace tracking algorithm has a better performance than the PAST algorithm for tracking fast-varying subspace and in an impulsive noise environment. © 2010 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/124680
ISSN
2015 Impact Factor: 1.136
2015 SCImago Journal Rankings: 0.747
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLiao, Ben_HK
dc.contributor.authorZhang, ZGen_HK
dc.contributor.authorChan, SCen_HK
dc.date.accessioned2010-10-31T10:48:09Z-
dc.date.available2010-10-31T10:48:09Z-
dc.date.issued2010en_HK
dc.identifier.citationIeee Transactions On Circuits And Systems Ii: Express Briefs, 2010, v. 57 n. 9, p. 740-744en_HK
dc.identifier.issn1549-7747en_HK
dc.identifier.urihttp://hdl.handle.net/10722/124680-
dc.description.abstractThe conventional projection approximation subspace tracking (PAST) algorithm is based on the recursive least-squares algorithm, and its performance will degrade considerably when the subspace rapidly changes and the additive noise is impulsive. This brief proposes a new robust Kalman filter-based subspace tracking algorithm to overcome these two limitations of the PAST algorithm. It is based on a new extension of the adaptive Kalman filter with variable number of measurements (KFVNM) for tracking fast-varying subspace. Furthermore, M-estimation is incorporated into this KFVNM algorithm to combat the adverse effects of impulsive noise. Simulation results show that the robust KFVNM-based subspace tracking algorithm has a better performance than the PAST algorithm for tracking fast-varying subspace and in an impulsive noise environment. © 2010 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE.-
dc.relation.ispartofIEEE Transactions on Circuits and Systems II: Express Briefsen_HK
dc.rightsIEEE Transactions on Circuits and Systems Part 2: Express Briefs. Copyright © IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2010 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.-
dc.subjectImpulsive noiseen_HK
dc.subjectKalman filteren_HK
dc.subjectKalman filter with variable number of measurements (KFVNM)en_HK
dc.subjectleast squaresen_HK
dc.subjectprojection approximation subspace tracking (PAST)en_HK
dc.titleA new robust Kalman filter-based subspace tracking algorithm in an impulsive noise environmenten_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1549-7747&volume=57&issue=9&spage=740&epage=744&date=2010&atitle=A+new+robust+Kalman+filter-based+subspace+tracking+algorithm+in+an+impulsive+noise+environment-
dc.identifier.emailZhang, ZG:zgzhang@eee.hku.hken_HK
dc.identifier.emailChan, SC:scchan@eee.hku.hken_HK
dc.identifier.authorityZhang, ZG=rp01565en_HK
dc.identifier.authorityChan, SC=rp00094en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/TCSII.2010.2056414en_HK
dc.identifier.scopuseid_2-s2.0-77956671139en_HK
dc.identifier.hkuros174335en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77956671139&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume57en_HK
dc.identifier.issue9en_HK
dc.identifier.spage740en_HK
dc.identifier.epage744en_HK
dc.identifier.isiWOS:000283267100017-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLiao, B=44661377800en_HK
dc.identifier.scopusauthoridZhang, ZG=8597618700en_HK
dc.identifier.scopusauthoridChan, SC=13310287100en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats