A Hybrid Smartphone Indoor Positioning Solution for Mobile LBS
Open Access
- 11 December 2012
- Vol. 12 (12), 17208-17233
- https://doi.org/10.3390/s121217208
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.Keywords
This publication has 29 references indexed in Scilit:
- Reliability considerations of multi-sensor multi-network pedestrian navigationIET Radar, Sonar & Navigation, 2012
- Sensing strides using EMG signal for pedestrian navigationGPS Solutions, 2010
- Intelligent Dynamic Radio Tracking in Indoor Wireless Local Area NetworksIEEE Transactions on Mobile Computing, 2009
- Learning Adaptive Temporal Radio Maps for Signal-Strength-Based Location EstimationIEEE Transactions on Mobile Computing, 2008
- GALE: An Enhanced Geometry-Assisted Location Estimation Algorithm for NLOS EnvironmentsIEEE Transactions on Mobile Computing, 2007
- A Taxonomy for Radio Location FingerprintingPublished by Springer Science and Business Media LLC ,2007
- Kernel-Based Positioning in Wireless Local Area NetworksIEEE Transactions on Mobile Computing, 2007
- Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile PositioningEURASIP Journal on Advances in Signal Processing, 2006
- Robust location using system dynamics and motion constraintsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- A Probabilistic Approach to WLAN User Location EstimationInternational Journal of Wireless Information Networks, 2002