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Marginalized particle PHD filters for multiple object Bayesian filtering

contributor authorPetetin, Yohan
contributor authorMorelande, Mark
contributor authorDesbouvries, Francois
date accessioned2020-03-13T00:12:39Z
date available2020-03-13T00:12:39Z
date issued2014
identifier issn0018-9251
identifier other6850148.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1138351?show=full
formatgeneral
languageEnglish
publisherIEEE
titleMarginalized particle PHD filters for multiple object Bayesian filtering
typeJournal Paper
contenttypeMetadata Only
identifier padid8320410
subject keywordsBayes methods
subject keywordsGaussian processes
subject keywordsMonte Carlo methods
subject keywordsmixture models
subject keywordsparticle filtering (numerical methods)
subject keywordsGM approximations
subject keywordsGaussian mixture approximations
subject keywordsSMC methods
subject keywordsmarginalized particle PHD filters
subject keywordsmultiple object Bayesian filtering
subject keywordsmultitarget filtering problem
subject keywordspartially linear substructure
subject keywordsprobability hypothesis density filter
subject keywordssequential Monte Carlo methods
subject keywordsstochastic systems
subject keywordsAdaptation models
subject keywordsApproximation methods
subject keywordsAtmospheric measurements
subject keywordsBayes methods
subject keywordsFiltering
subject keywordsParti
identifier doi10.1109/TAES.2014.120805
journal titleAerospace and Electronic Systems, IEEE Transactions on
journal volume50
journal issue2
filesize696626
citations1


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