Standardizing location fingerprints across heterogeneous mobile devices for indoor localization

Han Zou, Baoqi Huang, Xiaoxuan Lu, Hao Jiang, Lihua Xie

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

Abstract

The explosive proliferation of mobile devices and the popularity of social networks have spurred extensive demands on Location Based Services (LBSs) in recent decades. The IEEE 802.11 (WiFi) based Indoor Positioning Systems (IPSs) are gaining popularity because of the wide and ubiquitous availability of WiFi infrastructures in indoor environments. Most of IPSs are adopting the fingerprinting approach to mitigate pervasive indoor multipath effects. However, the heterogeneity of mobile devices significantly degrades the localization performance of the fingerprinting approach. In this paper, we apply the Procrustes analysis method to transform the WiFi received signal strengths (RSSs) to a new type of standard location fingerprints which are tolerant of the heterogeneity of various devices. Then, a robust indoor positioning algorithm based on the standardized location fingerprints and the weighted k nearest neighbor (WKN-N) method is proposed. Extensive experiments are carried out and show that the standardized location fingerprints and the proposed positioning system address the device heterogeneity issue satisfactorily.
Original languageEnglish
Title of host publication2016 IEEE Wireless Communications and Networking Conference
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-6
Number of pages6
ISBN (Electronic)978-1-4673-9814-5
ISBN (Print)978-1-4673-9815-2
DOIs
Publication statusPublished - 15 Sep 2016
Event2016 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2016 - Doha, Qatar
Duration: 3 Apr 20166 Apr 2016

Publication series

Name
PublisherIEEE
ISSN (Electronic)1558-2612

Conference

Conference2016 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2016
Country/TerritoryQatar
CityDoha
Period3/04/166/04/16

Keywords

  • Indoor Localization
  • Device Heterogeneity

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