Multi-Sensor Centralized Fusion Without Measurement Noise Covariance By Variational Bayesian Approximation

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dc.contributor.author Gao, X
dc.contributor.author Chen, JF
dc.contributor.author Tao, D
dc.contributor.author Li, X
dc.date.accessioned 2012-02-02T10:56:35Z
dc.date.issued 2011-01
dc.identifier.citation IEEE Transactions On Aerospace And Electronic Systems, 2011, 47 (1), pp. 718 - 727
dc.identifier.issn 0018-9251
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/15336
dc.description.abstract The work presented here solves the multi-sensor centralized fusion problem in the linear Gaussian model without the measurement noise variance. We generalize the variational Bayesian approximation based adaptive Kalman filter (VB_AKF) from the single sen
dc.publisher IEEE-Inst Electrical Electronics Engineers Inc
dc.relation.isbasedon 10.1109/TAES.2011.5705702
dc.title Multi-Sensor Centralized Fusion Without Measurement Noise Covariance By Variational Bayesian Approximation
dc.type Journal Article
dc.description.version Published
dc.parent IEEE Transactions On Aerospace And Electronic Systems
dc.journal.volume 1
dc.journal.volume 47
dc.journal.number 1 en_US
dc.publocation Piscataway, USA en_US
dc.identifier.startpage 718 en_US
dc.identifier.endpage 727 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 0906 Electrical and Electronic Engineering
dc.personcode 111502
dc.percentage 100 en_US
dc.classification.name Electrical and Electronic Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity WOS:000286931800048 en_US
dc.description.keywords Track Association; Particle Filters; Monte-Carlo; State; Parameters; Estimators; Tutorial en_US
dc.description.keywords Science & Technology
dc.description.keywords Life Sciences & Biomedicine
dc.description.keywords Biodiversity Conservation
dc.description.keywords Ecology
dc.description.keywords Environmental Sciences
dc.description.keywords Biodiversity & Conservation
dc.description.keywords Environmental Sciences & Ecology
dc.description.keywords BIODIVERSITY CONSERVATION
dc.description.keywords ECOLOGY
dc.description.keywords ENVIRONMENTAL SCIENCES
dc.description.keywords habitat suitability
dc.description.keywords modelling
dc.description.keywords spatial analysis
dc.description.keywords road-kill
dc.description.keywords common species
dc.description.keywords Vombatus ursinus
dc.description.keywords NEW-SOUTH-WALES
dc.description.keywords GROUND-DWELLING MAMMALS
dc.description.keywords EUCALYPT FORESTS
dc.description.keywords ECOLOGICAL TRAPS
dc.description.keywords SOCIAL-ORGANIZATION
dc.description.keywords CROSS-VALIDATION
dc.description.keywords LAND-USE
dc.description.keywords SUITABILITY
dc.description.keywords POPULATION
dc.description.keywords CONSEQUENCES
dc.description.keywords Track Association
dc.description.keywords Particle Filters
dc.description.keywords Monte-Carlo
dc.description.keywords State
dc.description.keywords Parameters
dc.description.keywords Estimators
dc.description.keywords Tutorial
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Strength - Quantum Computation and Intelligent Systems
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)


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