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Conference Paper: A new adaptive Kalman filter-based subspace tracking algorithm and its application to DOA estimation

TitleA new adaptive Kalman filter-based subspace tracking algorithm and its application to DOA estimation
Authors
KeywordsElectronics
Issue Date2006
PublisherIEEE.
Citation
Proceedings - Ieee International Symposium On Circuits And Systems, 2006, p. 129-132 How to Cite?
AbstractThis paper presents a new Kalman filter-based subspace tracking algorithm and its application to directions of arrival (DOA) estimation. An autoregressive (AR) process is used to describe the dynamics of the subspace and a new adaptive Kalman filter with variable measurements (KFYM) algorithm is developed to estimate the time-varying subspace recursively from the state-space model and the given observations. For stationary subspace, the proposed algorithm will switch to the conventional PAST to lower the computational complexity. Simulation results show that the adaptive subspace tracking method has a better performance than conventional algorithms in DOA estimation for a wide variety of experimental condition. © 2006 IEEE.
DescriptionIEEE International Symposium on Circuits and Systems, Island of Kos, Greece, 21-24 May 2006
Persistent Identifierhttp://hdl.handle.net/10722/45928
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorChan, SCen_HK
dc.contributor.authorZhang, ZGen_HK
dc.contributor.authorZhou, Yen_HK
dc.date.accessioned2007-10-30T06:38:41Z-
dc.date.available2007-10-30T06:38:41Z-
dc.date.issued2006en_HK
dc.identifier.citationProceedings - Ieee International Symposium On Circuits And Systems, 2006, p. 129-132en_HK
dc.identifier.issn0271-4310en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45928-
dc.descriptionIEEE International Symposium on Circuits and Systems, Island of Kos, Greece, 21-24 May 2006-
dc.description.abstractThis paper presents a new Kalman filter-based subspace tracking algorithm and its application to directions of arrival (DOA) estimation. An autoregressive (AR) process is used to describe the dynamics of the subspace and a new adaptive Kalman filter with variable measurements (KFYM) algorithm is developed to estimate the time-varying subspace recursively from the state-space model and the given observations. For stationary subspace, the proposed algorithm will switch to the conventional PAST to lower the computational complexity. Simulation results show that the adaptive subspace tracking method has a better performance than conventional algorithms in DOA estimation for a wide variety of experimental condition. © 2006 IEEE.en_HK
dc.format.extent1494073 bytes-
dc.format.extent27162 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofProceedings - IEEE International Symposium on Circuits and Systemsen_HK
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.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectElectronicsen_HK
dc.titleA new adaptive Kalman filter-based subspace tracking algorithm and its application to DOA estimationen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0271-4302&volume=&spage=129&epage=132&date=2006&atitle=A+new+adaptive+Kalman+filter-based+subspace+tracking+algorithm+and+its+application+to+DOA+estimationen_HK
dc.identifier.emailChan, SC: ascchan@hkucc.hku.hken_HK
dc.identifier.emailZhang, ZG: zhangzg@hku.hken_HK
dc.identifier.emailZhou, Y: yizhou@eee.hku.hken_HK
dc.identifier.authorityChan, SC=rp00094en_HK
dc.identifier.authorityZhang, ZG=rp01565en_HK
dc.identifier.authorityZhou, Y=rp00213en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ISCAS.2006.1692539en_HK
dc.identifier.scopuseid_2-s2.0-34547381035en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34547381035&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage129en_HK
dc.identifier.epage132en_HK
dc.identifier.scopusauthoridChan, SC=13310287100en_HK
dc.identifier.scopusauthoridZhang, ZG=8597618700en_HK
dc.identifier.scopusauthoridZhou, Y=55209555200en_HK

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