Indoor Positioning Using Federated Kalman Filter

dc.contributor.author Ayabakan, Tarık
dc.contributor.author Kerestecioğlu, Feza
dc.contributor.author Kerestecioğlu, Feza
dc.contributor.other Computer Engineering
dc.date.accessioned 2021-01-25T18:15:54Z
dc.date.available 2021-01-25T18:15:54Z
dc.date.issued 2018
dc.description.abstract In this paper, the performance of a multi-sensor fusion technique, namely Federated Kalman Filter (FKF) is studied in the context of indoor positioning problem. Kalman filters having centralized and decentralized structures are widely used in outdoor positioning and navigation applications. Global Positioning System (GPS) is the most commonly used system for outdoor positionin/navigation, which cannot be used indoors due to the signal loss. In this study, a decentralized structure for FKF is applied in indoor positioning problem by taking its outdoor navigation performance into consideration. Simulations are performed with distance measurements, which are assumed to be calculated by using Received Signal Strength (RSS). Results gathered via different simulations are evaluated as promising for future studies. en_US
dc.identifier.citationcount 0
dc.identifier.doi 10.1109/UBMK.2018.8566652 en_US
dc.identifier.endpage 488 en_US
dc.identifier.isbn 9781538678930
dc.identifier.scopus 2-s2.0-85060597135 en_US
dc.identifier.startpage 483 en_US
dc.identifier.uri https://hdl.handle.net/20.500.12469/3732
dc.identifier.uri https://doi.org/10.1109/UBMK.2018.8566652
dc.identifier.wos WOS:000511448500280 en_US
dc.institutionauthor Kerestecioǧlu, Feza en_US
dc.language.iso en en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.relation.journal UBMK 2018 - 3rd International Conference on Computer Science and Engineering en_US
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/embargoedAccess en_US
dc.scopus.citedbyCount 6
dc.subject data fusion en_US
dc.subject Federated Kalman filter en_US
dc.subject indoor positioning en_US
dc.title Indoor Positioning Using Federated Kalman Filter en_US
dc.type Conference Object en_US
dc.wos.citedbyCount 0
dspace.entity.type Publication
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