Particle filter for context sensitive indoor pedestrian navigation

Peltola, Pekka; Hill, Chris; Moore, Terry

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. (2016, June). Particle filter for context sensitive indoor pedestrian navigation. Presented at 2016 International Conference on Localization and GNSS, ICL-GNSS 2016, Barcelona, Spain

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2016 International Conference on Localization and GNSS, ICL-GNSS 2016
• Start Date: Jun 28, 2016
• End Date: Jun 30, 2016
• Acceptance Date: Jun 28, 2016
• Online Publication Date: Aug 8, 2016
• Publication Date: 2016
• Deposit Date: Sep 30, 2016
• Publicly Available Date: Sep 30, 2016
• Peer Reviewed: Peer Reviewed
• Series ISSN: 2325-0771
• Book Title: Proceedings of 2016 International Conference on Localization and GNSS (ICL-GNSS)
• ISBN: 978-1-5090-1757-7
• 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 systems; particle filter; pedestrian navigation; ultra-wideband technology
• Public URL: https://nottingham-repository.worktribe.com/output/806314
• Publisher URL: http://dx.doi.org/10.1109/ICL-GNSS.2016.7533865
• Contract Date: Sep 30, 2016