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Issue No.10 - Oct. (2013 vol.12)
pp: 2050-2062
Anthea Wain Sy Au , University of Toronto, Toronto
Chen Feng , University of Toronto, Toronto and Beijing Jiaotong University, Beijing
Shahrokh Valaee , University of Toronto, Toronto
Sophia Reyes , University of Toronto, Toronto
Sameh Sorour , University of Toronto, Toronto
Samuel N. Markowitz , University of Toronto, Toronto
Deborah Gold , The Canadian National Institute for the Blind, Toronto
Keith Gordon , The Canadian National Institute for the Blind, Toronto
Moshe Eizenman , University of Toronto, Toronto
An indoor tracking and navigation system based on measurements of received signal strength (RSS) in wireless local area network (WLAN) is proposed. In the system, the location determination problem is solved by first applying a proximity constraint to limit the distance between a coarse estimate of the current position and a previous estimate. Then, a Compressive Sensing-based (CS--based) positioning scheme, proposed in our previous work , , is applied to obtain a refined position estimate. The refined estimate is used with a map-adaptive Kalman filter, which assumes a linear motion between intersections on a map that describes the user's path, to obtain a more robust position estimate. Experimental results with the system that is implemented on a PDA with limited resources (HP iPAQ hx2750 PDA) show that the proposed tracking system outperforms the widely used traditional positioning and tracking systems. Meanwhile, the tracking system leads to 12.6 percent reduction in the mean position error compared to the CS-based stationary positioning system when three APs are used. A navigation module that is integrated with the tracking system provides users with instructions to guide them to predefined destinations. Thirty visually impaired subjects from the Canadian National Institute for the Blind (CNIB) were invited to further evaluate the performance of the navigation system. Testing results suggest that the proposed system can be used to guide visually impaired subjects to their desired destinations.
Kalman filters, Mobile communication, Vectors, Databases, Mobile handsets, Wireless LAN, Computational modeling, mobile devices, Kalman filters, Mobile communication, Vectors, Databases, Mobile handsets, Wireless LAN, Computational modeling, visually impaired, Indoor positioning, indoor tracking, real time, Kalman filter, $(\alpha \beta)$ filter, indoor navigation, compressive sensing, clustering, radio map, WLANs, RSS
Anthea Wain Sy Au, Chen Feng, Shahrokh Valaee, Sophia Reyes, Sameh Sorour, Samuel N. Markowitz, Deborah Gold, Keith Gordon, Moshe Eizenman, "Indoor Tracking and Navigation Using Received Signal Strength and Compressive Sensing on a Mobile Device", IEEE Transactions on Mobile Computing, vol.12, no. 10, pp. 2050-2062, Oct. 2013, doi:10.1109/TMC.2012.175
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