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Kalman filter with a linear state model for PDR+WLAN positioning and its application to assisting a particle filter

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Details

Original languageEnglish
Article number33
JournalEurasip Journal on Advances in Signal Processing
Volume2015
Issue number1
DOIs
Publication statusPublished - 1 Dec 2015
Publication typeA1 Journal article-refereed

Abstract

Indoor positioning based on wireless local area network (WLAN) signals is often enhanced using pedestrian dead reckoning (PDR) based on an inertial measurement unit. The state evolution model in PDR is usually nonlinear. We present a new linear state evolution model for PDR. In simulated-data and real-data tests of tightly coupled WLAN-PDR positioning, the positioning accuracy with this linear model is better than with the traditional models when the initial heading is not known, which is a common situation. The proposed method is computationally light and is also suitable for smoothing. Furthermore, we present modifications to WLAN positioning based on Gaussian coverage areas and show how a Kalman filter using the proposed model can be used for integrity monitoring and (re)initialization of a particle filter.

Keywords

  • Computational modeling, Indoor positioning, Pedestrian dead reckoning, Wireless LAN

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