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Basic techniques for filtering noise out of accelerometer data

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dc.title Basic techniques for filtering noise out of accelerometer data en
dc.contributor.author Kunčar, Aleš
dc.relation.ispartof Annals of DAAAM and Proceedings of the International DAAAM Symposium
dc.identifier.issn 1726-9679 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-902734-07-5
dc.date.issued 2015
utb.relation.volume 2015-January
dc.citation.spage 1122
dc.citation.epage 1128
dc.event.title 26th DAAAM International Symposium on Intelligent Manufacturing and Automation, DAAAM 2015
dc.event.location Zadar
utb.event.state-en Croatia
utb.event.state-cs Chorvatsko
dc.event.sdate 2015-10-21
dc.event.edate 2015-10-24
dc.type conferenceObject
dc.language.iso en
dc.publisher Danube Adria Association for Automation and Manufacturing, DAAAM
dc.identifier.doi 10.2507/26th.daaam.proceedings.158
dc.relation.uri http://doi.org/10.2507/26th.daaam.proceedings.045
dc.subject Accelerometer en
dc.subject Exponential moving average en
dc.subject Inertial sensors en
dc.subject Kalman filter en
dc.subject Simple moving average en
dc.description.abstract This research paper describes the evaluation of an indoor localization system based only on commercially availabl minimized low-cost micro-electro-mechanical (MEMS) inertial sensors. The low-cost inertial sensors are ver predisposed to noise and error. In order to filter out the noise, there must be applied some filtration algorithms. So, th aim of this research paper is to compare different filtration techniques to filter the noise out of measured data. Th techniques used in this experiment were simple moving average (SMA), exponential moving average (EMA) and simpl Kalman filter (KF). en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1006763
utb.identifier.obdid 43874075
utb.identifier.scopus 2-s2.0-84987657115
utb.source d-scopus
dc.date.accessioned 2016-12-22T16:19:07Z
dc.date.available 2016-12-22T16:19:07Z
dc.rights Attribution-NonCommercial 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Kunčar, Aleš
utb.fulltext.affiliation Ales Kuncar Tomas Bata University in Zlin, Faculty of Applied Informatics, Nad Stranemi 4511, Zlin 760 05, Czech Republic
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by Internal Grant Agency of Tomas Bata University in Zlin under the project No. IGA/FAI/2015/012. I would like to thank my colleague Tomas Urbanek for motivation and assistance with the research.
utb.fulltext.projects IGA/FAI/2015/012
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