Cooperative localization using posterior linearization belief propagation

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Garcia-Fernandez, Angel F.
dc.contributor.author Svensson, Lennart
dc.contributor.author Särkkä, Simo
dc.date.accessioned 2019-06-03T14:18:32Z
dc.date.available 2019-06-03T14:18:32Z
dc.date.issued 2018
dc.identifier.citation Garcia-Fernandez , A F , Svensson , L & Särkkä , S 2018 , ' Cooperative localization using posterior linearization belief propagation ' IEEE Transactions on Vehicular Technology , vol. 67 , no. 1 , pp. 832-836 . https://doi.org/10.1109/TVT.2017.2734683 en
dc.identifier.issn 0018-9545
dc.identifier.issn 1939-9359
dc.identifier.other PURE UUID: cb9cf6aa-2f7d-46bc-8c1b-52ac3b3d0ed7
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/cooperative-localization-using-posterior-linearization-belief-propagation(cb9cf6aa-2f7d-46bc-8c1b-52ac3b3d0ed7).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85028915909&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/34092730/ELEC_Garcia_Fernandez_etal_Cooperative_Localisation_Using_IEEETraVecTech_67_1_accepted.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/38373
dc.description.abstract This paper presents the posterior linearisation belief propagation (PLBP) algorithm for cooperative localisation in wireless sensor networks with nonlinear measurements. PLBP performs two steps iteratively: linearisation and belief propagation. At the linearisation step, the nonlinear functions are linearised using statistical linear regression with respect to the current beliefs. This SLR is performed in practice by using sigma-points drawn from the beliefs. In the second step, belief propagation is run on the linearised model. We show by numerical simulations how PLBP can outperform other algorithms in the literature. en
dc.format.extent 832-836
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartofseries IEEE Transactions on Vehicular Technology en
dc.relation.ispartofseries Volume 67, issue 1 en
dc.rights openAccess en
dc.subject.other Automotive Engineering en
dc.subject.other Aerospace Engineering en
dc.subject.other Computer Networks and Communications en
dc.subject.other Applied Mathematics en
dc.subject.other Electrical and Electronic Engineering en
dc.subject.other 113 Computer and information sciences en
dc.title Cooperative localization using posterior linearization belief propagation en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Electrical Engineering and Automation
dc.contributor.department Chalmers University of Technology
dc.contributor.department Department of Electrical Engineering and Automation en
dc.subject.keyword Approximation algorithms
dc.subject.keyword Bayes methods
dc.subject.keyword Belief propagation
dc.subject.keyword cooperative localisation
dc.subject.keyword Covariance matrices
dc.subject.keyword Gaussian message passing
dc.subject.keyword Gaussian noise
dc.subject.keyword Kalman filters
dc.subject.keyword Message passing
dc.subject.keyword posterior linearisation
dc.subject.keyword sigma points
dc.subject.keyword Automotive Engineering
dc.subject.keyword Aerospace Engineering
dc.subject.keyword Computer Networks and Communications
dc.subject.keyword Applied Mathematics
dc.subject.keyword Electrical and Electronic Engineering
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201906033458
dc.identifier.doi 10.1109/TVT.2017.2734683
dc.type.version acceptedVersion


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