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Particle filter and smoother for indoor localization

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Original languageEnglish
Title of host publicationInternational Conference on Indoor Positioning and Indoor Navigation, IPIN 2013, 28-31 Oct 2013, Montbéliard-Belfort, France
Place of PublicationPiscataway, NJ
Number of pages10
Publication statusPublished - 2013
Publication typeA4 Article in a conference publication

Publication series

NameInternational Conference on Indoor Positioning and Indoor Navigation


We present a real-time particle filter for 2D and 3D hybrid indoor positioning. It uses wireless local area network (WLAN) based position measurements, step and turn detection from a hand-held inertial sensor unit, floor plan restrictions, altitude change measurements from barometer and possibly other measurements such as occasional GNSS fixes. We also present a particle smoother, which uses future measurements to improve the position estimate for non-real-time applications. A lightweight fallback filter is run in the background for initialization, divergence monitoring and possibly re-initialization. In real-data tests the particle filter is more accurate and consistent than the methods that do not use floor plans. An example is shown on how smoothing helps to improve the filter estimate. Moreover, a floor change case is presented, in which the filter is capable of detecting the floor change and improving the 2D accuracy using the floor change information.

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