Bayesian methodology for target tracking using combined RSS and AoA measurements

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dc.contributor.authorTomic, Slavisa
dc.contributor.authorBeko, Marko
dc.contributor.authorDinis, Rui
dc.contributor.authorTuba, Milan
dc.contributor.authorBacanin, Nebojsa
dc.date.accessioned2019-08-26T14:29:49Z
dc.date.available2019-08-26T14:29:49Z
dc.date.issued2017
dc.descriptionPhysical Communication 25 (2017) pág.158–166pt
dc.description.abstractThis work addresses the target tracking problem based on received signal strength (RSS) and angle of arrival (AoA) measurements. The Bayesian methodology, which integrates the information given by observations with prior knowledge extracted from target motion model in order to enhance the estimation accuracy was employed. First, by converting the considered highly non-linear measurement model into a linear one, i.e., a novel linearization technique of the measurement model is proposed. The derived model is then merged with the prior knowledge, and a novel maximum a posteriori (MAP) estimator whose solution is given in closed-form is proposed. It is also shown that the Kalman filter (KF) can be directly applied on top of the linearized observation model, which results in a proposal of a novel KF algorithm. Furthermore, to the best of authors’ knowledge, this paper premierly presents the application of the extended KF (EKF) and the unscented KF (UKF) to the considered tracking problem, by applying first-order linearization technique to the original non-linear model, and by applying the unscented transformation to carefully selected sample points, respectively. Finally, importance weights are computed for a large number of randomly selected sample points to render a well-known particle filter (PF) solution. Simulation results show that the proposed algorithms perform better than a naive one which uses only information from observations. They also confirm the effectiveness of the proposed linearization technique in comparison with the existing one, reducing the estimation error for about 25%.en
dc.formatapplication/pdf
dc.identifier.issnISSN 1874-4907
dc.identifier.urihttp://hdl.handle.net/10437/9738
dc.language.isoengpt
dc.publisherElsevieren
dc.relation.ispartofseries10.1016/j.phycom.2017.10.005pt
dc.rightsopenAccess
dc.subjectTARGET TRACKINGen
dc.subjectRECEIVED SIGNAL STRENGTHen
dc.subjectANGLE OF ARRIVALen
dc.subjectKALMAN FILTERen
dc.subjectENGENHARIA ELETROTÉCNICApt
dc.subjectELECTROTECHNICAL ENGINEERINGen
dc.subjectFILTRO DE KALMANpt
dc.subjectTARGET TRACKINGpt
dc.subjectRECEIVED SIGNAL STRENGTHpt
dc.subjectANGLE OF ARRIVALpt
dc.titleBayesian methodology for target tracking using combined RSS and AoA measurementsen
dc.typearticleen

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