Autonomous signal source displacement detection and recalibration of fingerprinting-based indoor localization systems

Fingerprinting-based indoor localization systems rely on stable signal distribution characteristics of fixed signal sources for location estimation. However, indoor environments are not static and changes in the environment can lead to displacement of some signal sources, potentially causing a drop...

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Bibliographic Details
Published in2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN) pp. 1 - 8
Main Authors Ngewi Fet, Handte, Marcus, Marron, Pedro Jose
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2017
Subjects
Calibration
Displacement measurement
Fingerprint recognition
Indoor environments
Manuals
Wireless LAN
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Summary:Fingerprinting-based indoor localization systems rely on stable signal distribution characteristics of fixed signal sources for location estimation. However, indoor environments are not static and changes in the environment can lead to displacement of some signal sources, potentially causing a drop in the localization performance. It is therefore necessary to regularly monitor the signal sources and manually recalibrate any whose signal distribution has changed. The effort for calibrating these systems is typically high, especially for large indoor environments. This paper proposes an approach for autonomously detecting the displacement of a signal source using only measurements collected by active users of the system. The proposed approach is demonstrated to reliably detect displaced signal sources as well as multiple simultaneous displacements of up to half of the deployed signals sources. It is further shown that the same measurements can be used to autonomously recalibrate the (WLAN- or Bluetooth-based) indoor localization system, achieving localization performance comparable to manual calibration.
ISSN:2471-917X
DOI:10.1109/IPIN.2017.8115906