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Particle filtering algorithms for tracking an acoustic source in a reverberant enrironment

Ward, Darren B; Lehmann, Eric; Williamson, Robert

Description

Traditional acoustic source localization algorithms attempt to find the current location of the acoustic source using data collected at an array of sensors at the current time only. In the presence of strong multipath, these traditional algorithms often erroneously locate a multipath reflection rather than the true source location. A recently proposed approach that appears promising in overcoming this drawback of traditional algorithms, is a state-space approach using particle filtering. In...[Show more]

dc.contributor.authorWard, Darren B
dc.contributor.authorLehmann, Eric
dc.contributor.authorWilliamson, Robert
dc.date.accessioned2015-12-08T22:34:07Z
dc.identifier.issn1063-6676
dc.identifier.urihttp://hdl.handle.net/1885/34935
dc.description.abstractTraditional acoustic source localization algorithms attempt to find the current location of the acoustic source using data collected at an array of sensors at the current time only. In the presence of strong multipath, these traditional algorithms often erroneously locate a multipath reflection rather than the true source location. A recently proposed approach that appears promising in overcoming this drawback of traditional algorithms, is a state-space approach using particle filtering. In this paper we formulate a general framework for tracking an acoustic source using particle filters. We discuss four specific algorithms that fit within this framework, and demonstrate their performance using both simulated reverberant data and data recorded in a moderately reverberant office room (with a measured reverberation time of 0.39 s). The results indicate that the proposed family of algorithms are able to accurately track a moving source in a moderately reverberant room.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.sourceIEEE Transactions on Speech and Audio Processing
dc.subjectKeywords: Acoustic signal processing; Algorithms; Data reduction; Delay circuits; Microphones; Seismology; Sensors; Signal filtering and prediction; Particle filtering; Speech processing Acoustic signal processing; Generalized cross-correlation; Localization; Particle filters; Time-delay estimation
dc.titleParticle filtering algorithms for tracking an acoustic source in a reverberant enrironment
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume11
dc.date.issued2003
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.ariespublicationU8803936xPUB118
local.type.statusPublished Version
local.contributor.affiliationWard, Darren B, Imperial College London
local.contributor.affiliationLehmann, Eric, College of Engineering and Computer Science, ANU
local.contributor.affiliationWilliamson, Robert, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.issue6
local.bibliographicCitation.startpage826
local.bibliographicCitation.lastpage836
local.identifier.doi10.1109/TSA.2003.818112
dc.date.updated2015-12-08T09:40:57Z
local.identifier.scopusID2-s2.0-0347337998
CollectionsANU Research Publications

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