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Particle filter for context sensitive indoor pedestrian navigation

Peltola, Pekka; Hill, Chris; Moore, Terry

Authors

Pekka Peltola

Chris Hill

Terry Moore



Abstract

Novel particle filter design combines foot mounted inertial (IMU), bluetooth low energy (BLE) and ultra-wideband (UWB) technologies along with map matching into a seamless integrated navigation system for indoors. The system was evaluated by 10 test walks along an 80m long indoor track including stairs and running. 95% of the time the average error for a particle was below 3.1 m with filter completion success rate of 90%. Furthermore, a system without UWB using only IMU, BLE and map matching achieved an average error for a particle to be below 3.6 m with filter completion success rate of 70%. The selected technologies and sensors are affordable and easily deployable. Inertial measurement unit's characteristics complement the disadvantages in the rf technologies and vice versa. The code for the rover can be implemented on a modern mobile device together with a foot mounted IMU.

Citation

Peltola, P., Hill, C., & Moore, T. (in press). Particle filter for context sensitive indoor pedestrian navigation. In 2016 International Conference on Localization and GNSS (ICL-GNSS). https://doi.org/10.1109/ICL-GNSS.2016.7533865

Conference Name 2016 International Conference on Localization and GNSS, ICL-GNSS 2016
End Date Jun 30, 2016
Acceptance Date Jun 28, 2016
Online Publication Date Aug 8, 2016
Deposit Date Sep 30, 2016
Publicly Available Date Sep 30, 2016
Peer Reviewed Peer Reviewed
Book Title 2016 International Conference on Localization and GNSS (ICL-GNSS)
DOI https://doi.org/10.1109/ICL-GNSS.2016.7533865
Keywords Bandpass filters; global positioning system; indoor postioning systems; mobile devices; monte carlo methods; navigation systems; units of measurement; bluetooth low energies (ble); context sensitive; inertial measurement unit; integrated navigation system
Public URL http://eprints.nottingham.ac.uk/id/eprint/37288
Publisher URL http://dx.doi.org/10.1109/ICL-GNSS.2016.7533865
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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