Integration of IMU in indoor positioning systems with non-Gaussian ranging error distributions

Shenghong Li, Mark Hedley, Iain B. Collings, Mark Johnson

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

4 Citations (Scopus)

Abstract

The performance of a wireless positioning system can be improved through the integration with an inertial measurement unit (IMU). Conventional sensor fusion algorithms based on a Kalman filter (KF) are not accurate for indoor positioning systems since the ranging errors in indoor environments are non-Gaussian distributed due to non-line-of-sight (NLOS) and multipath propagation. In this paper, we propose a novel sensor fusion scheme for integrating range-based indoor positioning systems with IMUs, which supports non-Gaussian ranging error distributions at a low computational cost by using a pseudo position measurement for the measurement update step in the KF. The performance of the proposed fusion scheme is evaluated experimentally using an indoor positioning platform in an office environment, and is shown to be significantly better than conventional approaches. Particularly, the median positioning error is reduced by 52% using the proposed scheme, and the maximum positioning error is reduced to 0.36 m using an offline tracking algorithm extended from the proposed approach.

Original languageEnglish
Title of host publicationProceedings of the IEEE/ION Position, Location and Navigation Symposium, PLANS 2016
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages577-583
Number of pages7
ISBN (Electronic)9781509020423
DOIs
Publication statusPublished - 26 May 2016
EventIEEE/ION Position, Location and Navigation Symposium, PLANS 2016 - Savannah, Georgia
Duration: 11 Apr 201614 Apr 2016

Other

OtherIEEE/ION Position, Location and Navigation Symposium, PLANS 2016
CountryGeorgia
CitySavannah
Period11/04/1614/04/16

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Li, S., Hedley, M., Collings, I. B., & Johnson, M. (2016). Integration of IMU in indoor positioning systems with non-Gaussian ranging error distributions. In Proceedings of the IEEE/ION Position, Location and Navigation Symposium, PLANS 2016 (pp. 577-583). [7479748] Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/PLANS.2016.7479748