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Graph-Based Map Matching for Indoor Positioning

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

Details

Original languageEnglish
Title of host publication10th International Conference on Information, Communications and Signal Processing (ICICS)
PublisherIEEE
Number of pages5
ISBN (Electronic)9781467372176
DOIs
Publication statusPublished - 1 Dec 2015
Publication typeA4 Article in a conference publication
EventInternational Conference on Information, Communications and Signal Processing -
Duration: 1 Jan 1900 → …

Conference

ConferenceInternational Conference on Information, Communications and Signal Processing
Period1/01/00 → …

Abstract

This article presents a probabilistic motion model that is based on an economical graph-based indoor map representation, such that the motion of the user is constrained according to the floor plan of a building. The floor plan is modeled as a combination of links and open space polygons that are connected by nodes. In the authors’ earlier work the link transition probabilities in this graph are proportional to the total link lengths that are the total lengths of the subgraphs accessible by choosing the considered link option, and this article extends this model to include open space polygons as well. A particle filter using the extended motion model in which all particles are constrained according to the map structure is presented. Furthermore, wireless local area network and Bluetooth Low Energy positioning tests show that the proposed algorithm outperforms comparison methods especially if the measurement rate is low.

Keywords

  • Indoor positioning, particle filter, motion model, map matching, graph

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