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Sensors 2015, 15(4), 7096-7124; doi:10.3390/s150407096

A Floor-Map-Aided WiFi/Pseudo-Odometry Integration Algorithm for an Indoor Positioning System

1
School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
2
Sino-UK Geospatial Engineering Centre, The University of Nottingham, Nottingham NG7, 2RD, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Kourosh Khoshelham and Sisi Zlatanova
Received: 28 November 2014 / Accepted: 17 March 2015 / Published: 24 March 2015
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)

Abstract

This paper proposes a scheme for indoor positioning by fusing floor map, WiFi and smartphone sensor data to provide meter-level positioning without additional infrastructure. A topology-constrained K nearest neighbor (KNN) algorithm based on a floor map layout provides the coordinates required to integrate WiFi data with pseudo-odometry (P-O) measurements simulated using a pedestrian dead reckoning (PDR) approach. One method of further improving the positioning accuracy is to use a more effective multi-threshold step detection algorithm, as proposed by the authors. The “go and back” phenomenon caused by incorrect matching of the reference points (RPs) of a WiFi algorithm is eliminated using an adaptive fading-factor-based extended Kalman filter (EKF), taking WiFi positioning coordinates, P-O measurements and fused heading angles as observations. The “cross-wall” problem is solved based on the development of a floor-map-aided particle filter algorithm by weighting the particles, thereby also eliminating the gross-error effects originating from WiFi or P-O measurements. The performance observed in a field experiment performed on the fourth floor of the School of Environmental Science and Spatial Informatics (SESSI) building on the China University of Mining and Technology (CUMT) campus confirms that the proposed scheme can reliably achieve meter-level positioning. View Full-Text
Keywords: WiFi/pseudo-odometry; extended kalman filter; particle filter; floor map WiFi/pseudo-odometry; extended kalman filter; particle filter; floor map
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Wang, J.; Hu, A.; Liu, C.; Li, X. A Floor-Map-Aided WiFi/Pseudo-Odometry Integration Algorithm for an Indoor Positioning System. Sensors 2015, 15, 7096-7124.

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