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Robust pedestrian dead reckoning using anchor point recalibration

Title data

Hoffmann, Eike Jens ; Schauer, Lorenz ; Schönfeld, Mirco ; Kraus, Maximilian:
Robust pedestrian dead reckoning using anchor point recalibration.
In: Institute of Electrical and Electronics Engineers (ed.): 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN). - Piscataway, NJ : IEEE , 2017 . - 7 S.
ISBN 978-1-5090-6300-0
DOI: https://doi.org/10.1109/IPIN.2017.8115948

Official URL: Volltext

Abstract in another language

All indoor positioning approaches face the challenge to deal with erroneous input data from sensors. Especially independent systems like dead reckoning rely on highly accurate input data from accelerometers and gyroscopes for an accurate prediction of the user's position. But with the widespread of affordable mobile devices equipped with low-cost sensors, the obtained input data is noisy and of poor quality. Since errors accumulate within a pedestrian dead reckoning (PDR) system, there is an inevitable need for recalibration on a regular basis. We propose a PDR system based on state-of-the-art particle filters, which is recalibrated using both anchor points and a pedestrian movement model. Our evaluation compares standard particle filters with a backtracking particle filter including information from indoor maps and our enhancements. We show that a combination of anchor point recalibration, error calculation of sensor bias, and a fine-tuned movement model can decrease the RMSE by 1.07 m.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Buildings; Dead reckoning; Position measurement; Sensor systems; Trajectory; Wireless fidelity
Institutions of the University: Faculties > Faculty of Languages and Literature
Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung
Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung - Juniorprof. Dr. Mirco Schönfeld
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 18 Nov 2021 10:23
Last Modified: 18 Nov 2021 10:23
URI: https://eref.uni-bayreuth.de/id/eprint/67888