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Sensors 2012, 12(12), 17208-17233; doi:10.3390/s121217208

A Hybrid Smartphone Indoor Positioning Solution for Mobile LBS

Department of Navigation and Positioning, Finnish Geodetic Institute, Geodeetinrinne 2, Masala 02431, Finland
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Received: 29 October 2012 / Revised: 6 December 2012 / Accepted: 7 December 2012 / Published: 12 December 2012
(This article belongs to the Section Sensor Networks)
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Abstract

Smartphone positioning is an enabling technology used to create new business in the navigation and mobile location-based services (LBS) industries. This paper presents a smartphone indoor positioning engine named HIPE that can be easily integrated with mobile LBS. HIPE is a hybrid solution that fuses measurements of smartphone sensors with wireless signals. The smartphone sensors are used to measure the user’s motion dynamics information (MDI), which represent the spatial correlation of various locations. Two algorithms based on hidden Markov model (HMM) problems, the grid-based filter and the Viterbi algorithm, are used in this paper as the central processor for data fusion to resolve the position estimates, and these algorithms are applicable for different applications, e.g., real-time navigation and location tracking, respectively. HIPE is more widely applicable for various motion scenarios than solutions proposed in previous studies because it uses no deterministic motion models, which have been commonly used in previous works. The experimental results showed that HIPE can provide adequate positioning accuracy and robustness for different scenarios of MDI combinations. HIPE is a cost-efficient solution, and it can work flexibly with different smartphone platforms, which may have different types of sensors available for the measurement of MDI data. The reliability of the positioning solution was found to increase with increasing precision of the MDI data. View Full-Text
Keywords: smartphone positioning; mobile LBS; probabilistic algorithms; sensor fusion; ubiquitous computing smartphone positioning; mobile LBS; probabilistic algorithms; sensor fusion; ubiquitous computing
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Liu, J.; Chen, R.; Pei, L.; Guinness, R.; Kuusniemi, H. A Hybrid Smartphone Indoor Positioning Solution for Mobile LBS. Sensors 2012, 12, 17208-17233.

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