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Performance Analysis of Two-Dimensional Dead Reckoning Based on Vehicle Dynamic Sensors during GNSS Outages
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dc.contributor.author Han, Joong-Hee -
dc.contributor.author Park, Chi-Ho -
dc.contributor.author Hong, Chang-Ki -
dc.contributor.author Kwon, Jay Hyoun -
dc.date.available 2017-10-06T08:22:48Z -
dc.date.created 2017-10-06 -
dc.date.issued 2017-01 -
dc.identifier.issn 1687-725X -
dc.identifier.uri http://hdl.handle.net/20.500.11750/4562 -
dc.description.abstract Recently, to improve safety and convenience in driving, numerous sensors are mounted on cars to operate advanced driver assistant systems. Among various sensors, vehicle dynamic sensors can measure the vehicle motions such as speed and rotational angular speed for dead reckoning, which can be applied to develop a land vehicle positioning system to overcome the weaknesses of the GNSS technique. In this paper, three land vehicle positioning algorithms that integrate GNSS with vehicle dynamic sensors including a wheel speed sensor (WSS), a yaw rate sensor (YRS), and a steering angle sensor (SAS) are implemented, and then a performance evaluation was conducted during GNSS outages. Using a loosely coupled strategy, three integration algorithms are designed, namely, GNSS/WSS, GNSS/WSS/YRS, and GNSS/WSS/YRS/SAS. The performance of the three types of integration algorithm is evaluated based on two data sets. The results indicate that both the GNSS/WSS/YRS integration and the GNSS/WSS/YRS/SAS integration could estimate the horizontal position with meter-level accuracy during 30-second GNSS outages. However, the GNSS/WSS integration would provide an unstable navigation solution during GNSS outages due to the accuracy limitation of the computed yaw rate using WSS. © 2017 Joong-hee Han et al. -
dc.language English -
dc.publisher Wiley -
dc.title Performance Analysis of Two-Dimensional Dead Reckoning Based on Vehicle Dynamic Sensors during GNSS Outages -
dc.type Article -
dc.identifier.doi 10.1155/2017/9802610 -
dc.identifier.wosid 000410965200001 -
dc.identifier.scopusid 2-s2.0-85029683675 -
dc.identifier.bibliographicCitation Journal of Sensors, v.2017, no.1, pp.9802610 -
dc.description.isOpenAccess TRUE -
dc.subject.keywordPlus Fusio -
dc.subject.keywordPlus Kalman Filter -
dc.subject.keywordPlus Localization -
dc.subject.keywordPlus Navigation -
dc.citation.number 1 -
dc.citation.startPage 9802610 -
dc.citation.title Journal of Sensors -
dc.citation.volume 2017 -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.relation.journalResearchArea Engineering; Instruments & Instrumentation -
dc.relation.journalWebOfScienceCategory Engineering, Electrical & Electronic; Instruments & Instrumentation -
dc.type.docType Article -
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