Paper Info
Title
Integrated WiFi/PDR/Smartphone Using an Adaptive System Noise Extended Kalman Filter Algorithm for Indoor Localization.
Abstract
Wireless signal strength is susceptible to the phenomena of interference, jumping, and instability, which often appear in the positioning results based on Wi-Fi field strength fingerprint database technology for indoor positioning. Therefore, a Wi-Fi and PDR (pedestrian dead reckoning) real-time fusion scheme is proposed in this paper to perform fusing calculation by adaptively determining the dynamic noise of a filtering system according to pedestrian movement (straight or turning), which can effectively restrain the jumping or accumulation phenomena of wireless positioning and the PDR error accumulation problem. Wi-Fi fingerprint matching typically requires a quite high computational burden: To reduce the computational complexity of this step, the affinity propagation clustering algorithm is adopted to cluster the fingerprint database and integrate the information of the position domain and signal domain of respective points. An experiment performed in a fourth-floor corridor at the School of Environment and Spatial Informatics, China University of Mining and Technology, shows that the traverse points of the clustered positioning system decrease by 65%-80%, which greatly improves the time efficiency. In terms of positioning accuracy, the average error is 4.09 m through the Wi-Fi positioning method. However, the positioning error can be reduced to 2.32 m after integration of the PDR algorithm with the adaptive noise extended Kalman filter (EKF).
Year
DOI
Venue
2016
10.3390/ijgi5020008
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
Field
DocType
indoor positioning,affinity propagation clustering,feature fusion,pedestrian dead reckoning,multi-sensor fusion
Computer vision,Extended Kalman filter,Computer science,Adaptive system,Filter (signal processing),Fingerprint,Dead reckoning,Artificial intelligence,Positioning system,Traverse,Computational complexity theory
Journal
Volume
Issue
ISSN
5
2
2220-9964
Citations 
PageRank 
References 
19
1.09
12
Authors
5
Name
Order
Citations
PageRank
Xin Li1644.61
jian wang2523.53
Chunyan Liu3533.77
Liwen Zhang4256.25
Zheng-Kui Lin5191.09