Indoor Localization Method Based on Sequential Motion Tracking Using Topological Path Map

Yu Cheol Lee, Hyun Myung

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This paper proposes a novel indoor localization method based on sequential motion tracking (SMT) using a topological path map that can improve the shortcomings of traditional methods using range-only measurement sensors. The proposed method consists of map generation and location estimation. First, in the map preparation, we present the construction method of a radio fingerprint map and the topological path map. The radio fingerprint map contains radio signals moderated by a median filter, and the topological path map includes possible path motions in the form of nodes and edges using a floorplan drawing. Second, for location estimation, fingerprint analysis and SMT methods are developed. Fingerprint analysis finds the global region based on a histogram evaluation between the radio fingerprint map and online observations, which rely on Wi-Fi. The SMT determines the optimal position on the topological path map by considering the historical motion data and the fingerprint analysis result. Finally, the experimental results show that the proposed method is robust to the uncertainty of the fingerprint analysis using the range sensors and that it can accurately track global positions with efficient computations.

Original languageEnglish
Article number6287639
Pages (from-to)46187-46197
Number of pages11
JournalIEEE Access
Volume7
DOIs
StatePublished - 2019

Keywords

  • Fingerprint analysis
  • indoor localization
  • range measurement sensor
  • sequential motion tracking
  • topological path map

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