Geometric Dilution of Localization and Bias-Correction Methods

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dc.contributor.authorJi, Yiming
dc.contributor.authorYu, Changbin (Brad)
dc.contributor.authorAnderson, Brian
dc.coverage.spatialXiamen China
dc.date.accessioned2015-12-10T22:53:21Z
dc.date.createdJune 9-11 2010
dc.date.issued2010
dc.date.updated2016-02-24T11:01:19Z
dc.description.abstractA particular geometric problem-the collinearity problem-which may prevent effective use of localization algorithms is described in detail in this paper. Further analysis illustrates the methods for improving the estimate for localization algorithms also can be affected by the collinearity problem. In this paper, we propose a novel approach to deal with the collinearity problem for a localization improvement method-the bias-correction method [1, 2, 3]. Compare to earlier work such as [4], the main feature of the proposed approach is that it takes the level of the measurement noise into consideration as a variable. Monte Carlo simulation results demonstrate the performance of the proposed method. Further simulation illustrates the influence of two factors on the effect of the bias-correct method: the distance between sensors and the level of noise. Though it mainly aims to the bias-correction method, the proposed approach is also valid for localization algorithms because of the consistent performance of localization algorithms and the bias-correction method.
dc.identifier.isbn9781424451968
dc.identifier.urihttp://hdl.handle.net/1885/59316
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesInternational Conference on Control and Automation (ICCA 2010)
dc.sourceProceedings of International Conference on Control and Automation (ICCA 2010)
dc.subjectKeywords: Bias correction; Collinearity; Consistent performance; Geometric problems; Improvement methods; Localization algorithm; Measurement Noise; Monte Carlo Simulation; Algorithms; Computer simulation; Electromagnetic wave attenuation; Monte Carlo methods
dc.titleGeometric Dilution of Localization and Bias-Correction Methods
dc.typeConference paper
local.bibliographicCitation.lastpage583
local.bibliographicCitation.startpage578
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.authoremailu4468702@anu.edu.au
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.absfor080503 - Networking and Communications
local.identifier.absseo810104 - Emerging Defence Technologies
local.identifier.ariespublicationu4334215xPUB484
local.identifier.doi10.1109/ICCA.2010.5524109
local.identifier.scopusID2-s2.0-77957857870
local.identifier.uidSubmittedByu4334215
local.type.statusPublished Version

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