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dc.contributor.authorErofeeva, Victoria
dc.contributor.authorGranichin, Oleg
dc.contributor.authorIvanskiy, Yury
dc.contributor.authorJiang, Yuming
dc.contributor.authorProskurnikov, Anton
dc.contributor.authorSergeenko, Anna
dc.date.accessioned2021-09-10T05:49:43Z
dc.date.available2021-09-10T05:49:43Z
dc.date.created2021-01-13T11:07:19Z
dc.date.issued2020
dc.identifier.citationIFAC-PapersOnLine. 2020, .en_US
dc.identifier.issn2405-8963
dc.identifier.urihttps://hdl.handle.net/11250/2775038
dc.description.abstractWe consider a dynamic network of sensors that cooperate to estimate parameters of multiple targets. Each sensor can observe parameters of a few targets, reconstructing the trajectories of the remaining targets via interactions with “neighbouring” sensors. The multi-target tracking has to be provided in the face of uncertainties, which include unknown-but-bounded drift of parameters, noise in observations and distortions introduced by communication channels. To provide tracking in presence of these uncertainties, we employ a distributed algorithm, being an “offspring” of a consensus protocol and the stochastic gradient descent. The mathematical results on the algorithm’s convergence are illustrated by numerical simulations.en_US
dc.language.isoengen_US
dc.publisherInternational Federation of Automatic Control (IFAC)en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleConsensus-based Distributed Algorithm for Multisensor-Multitarget Tracking under Unknown-but-Bounded Disturbancesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber7en_US
dc.source.journalIFAC-PapersOnLineen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.ifacol.2020.12.1756
dc.identifier.cristin1870447
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal