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Integrated WiFi/PDR/Smartphone using an unscented Kalman filter algorithm for 3D indoor localization

Chen, Guoliang; Meng, Xiaolin; Wang, Yunjia; Zhang, Yanzhe; Tian, Peng

Authors

Guoliang Chen

Xiaolin Meng xiaolin.meng@nottingham.ac.uk

Yunjia Wang

Yanzhe Zhang

Peng Tian



Abstract

Because of the high calculation cost and poor performance of a traditional planar map when dealing with complicated indoor geographic information, a WiFi fingerprint indoor positioning system cannot be widely employed on a smartphone platform. By making full use of the hardware sensors embedded in the smartphone, this study proposes an integrated approach to a three-dimensional (3D) indoor positioning system. First, an improved K-means clustering method is adopted to reduce the fingerprint database retrieval time and enhance positioning efficiency. Next, with the mobile phone’s acceleration sensor, a new step counting method based on auto-correlation analysis is proposed to achieve cell phone inertial navigation positioning. Furthermore, the integration of WiFi positioning with Pedestrian Dead Reckoning (PDR) obtains higher positional accuracy with the help of the Unscented Kalman Filter algorithm. Finally, a hybrid 3D positioning system based on Unity 3D, which can carry out real-time positioning for targets in 3D scenes, is designed for the fluent operation of mobile terminals.

Journal Article Type Article
Publication Date Sep 23, 2015
Journal Sensors
Electronic ISSN 1424-8220
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 15
Issue 9
APA6 Citation Chen, G., Meng, X., Wang, Y., Zhang, Y., & Tian, P. (2015). Integrated WiFi/PDR/Smartphone using an unscented Kalman filter algorithm for 3D indoor localization. Sensors, 15(9), https://doi.org/10.3390/s150924595
DOI https://doi.org/10.3390/s150924595
Keywords Indoor localization; WiFi/PDR; Clustering; Auto-correlation analysis; Unscented Kalman Filter; Unity 3D
Publisher URL http://www.mdpi.com/1424-8220/15/9/24595
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0



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