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dc.contributor.authorAyabakan, Tarık
dc.contributor.authorKerestecioǧlu, Feza
dc.date.accessioned2020-12-24T13:29:06Z
dc.date.available2020-12-24T13:29:06Z
dc.date.issued2019
dc.identifier.isbn978-172813964-7
dc.identifier.urihttps://doi.org/10.1109/UBMK.2019.8907082en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12469/3656
dc.description.abstractIn this paper, the performance of three different kinds of Kalman Filter (KF) structure: Single Kalman Filter (SKF)(which filters data of a single sensor), Centralized Kalman Filter (CKF) and Federated Kalman Filter (FKF) are studied considering the indoor positioning problem. Kalman filters are widely used in outdoor positioning and navigation applications providing good results. For multi-sensor applications, KF has centralized and decentralized structures. In this study, multisensor and single-sensor dedicated Kalman filter structures FKF, CKF and SKF are applied in indoor positioning problem by taking its outdoor navigation performance into consideration. Received Signal Strength (RSS) data are generated, from which distance information, a vital part of the simulations, are obtained. Three different noise levels are used to assess performance of filters. Results gathered via different simulations showed that multi-sensor structures provide a better solution than single sensor structures.en_US
dc.language.isoEnglishen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectdata fusionen_US
dc.subjectindoor positioningen_US
dc.subjectKalman filteren_US
dc.subjectmulti-sensor systemsen_US
dc.titleMulti-Sensor Indoor Positioningen_US
dc.typeConference Paperen_US
dc.identifier.startpage330en_US
dc.identifier.endpage335en_US
dc.relation.journalUBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineeringen_US
dc.identifier.volumeSeptember 2019en_US
dc.identifier.doi10.1109/UBMK.2019.8907082en_US
dc.contributor.khasauthorKerestecioǧlu, Fezaen_US


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