Abstract
Location information has become crucial in many circumstances such as rescue operations, emergencies, navigation, and tracking. Furthermore, with the deployment of the wireless communication networks and the mobility that characterizes the wireless communication users, positioning information has become a great interest. Location tracking, based on received signal strength indicators (RSSI), is a cost efficient method to gather location information. However, RSSI suffers from estimation errors due to shadowing. In this paper, a positioning framework for location tracking in WLAN IEEE 802.11n networks has been proposed which is transparent to accuracy improvement technologies. Furthermore, a novel Kalman filter implementation is presented. The implementation brings advantages over the most common approach “extended Kalman filter” in terms of computational efforts and does not require the linearization steps. The positioning framework and the proposed implementation of the Kalman filter have been evaluated on experimental data using Monte Carlo simulation.
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