Abstract
An indoor positioning and navigation system based on measurements of received signal strength in wireless local area network is proposed. In the system, the location determination problem is solved by applying compressive sensing, which offers recovery of sparse signals from a small number of noisy measurements by solving an l1-minimization problem. The refined estimate is then used with a map-adaptive Kalman filter for real-time tracking. A navigation module integrated with the tracking system guides users to pre-defined destinations with voice instructions. Experimental results with a system that was implemented on a PDA shows that the proposed tracking system is lightweight so that it can be used on a resource constrained platform while outperforming the widely used traditional positioning and tracking systems. A pilot study was carried out with 30 visually impaired subjects from the Canadian National Institute for the Blind. Testing results show that the proposed system can be used to guide visually impaired subjects to their desired destinations with a very high success rate.
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