Bias Reduction Based on Maximum Likelihood Estimates with Application in Scan-based Localization

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dc.contributor.authorJi, Yiming
dc.contributor.authorYu, Changbin (Brad)
dc.contributor.authorAnderson, Brian
dc.coverage.spatialXi'an China
dc.date.accessioned2015-12-10T23:18:35Z
dc.date.createdJuly 26-28 2013
dc.date.issued2013
dc.date.updated2015-12-10T10:07:34Z
dc.description.abstractIn this paper, a novel bias reduction method is proposed to analytically express and reduce the bias arising in localization problems, thereby improving the localization accuracy. The proposed bias reduction method mixes Taylor series and a maximum likeli
dc.identifier.isbn9781479900305
dc.identifier.urihttp://hdl.handle.net/1885/65695
dc.publisherIEEE Control Systems Society
dc.relation.ispartofseries32nd Chinese Control Conference (CCC)
dc.sourceBias Reduction Based on Maximum Likelihood Estimates with Application in Scan-based Localization
dc.source.urihttp://www.proceedings.com/19738.html
dc.titleBias Reduction Based on Maximum Likelihood Estimates with Application in Scan-based Localization
dc.typeConference paper
local.bibliographicCitation.lastpage7376
local.bibliographicCitation.startpage7371
local.contributor.affiliationJi, Yiming, College of Engineering and Computer Science, ANU
local.contributor.affiliationYu, Changbin (Brad), College of Engineering and Computer Science, ANU
local.contributor.affiliationAnderson, Brian, College of Engineering and Computer Science, ANU
local.contributor.authoruidJi, Yiming, u4468702
local.contributor.authoruidYu, Changbin (Brad), u4168516
local.contributor.authoruidAnderson, Brian, u8104642
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor090609 - Signal Processing
local.identifier.absseo810104 - Emerging Defence Technologies
local.identifier.ariespublicationu4334215xPUB1145
local.identifier.scopusID2-s2.0-84890503842
local.type.statusPublished Version

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