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PIERLUIGI GALLO

RSS-eye: Human-assisted Indoor Localization without Radio Maps

Abstract

The pervasive diffusion of smartphones is boosting indoor positioning solutions and location-based services. We propose a novel methodology to perform indoor positioning of mobile users by the estimation of angles of arrival from access points whose locations are known. Angles of arrival are estimated by correlating WiFi RSSI measurements with data coming from a digital compass, which is provided by most current handsets. Our system has minimal requirements in terms of infrastructure and mobile hardware. The system neither needs calibration, nor radio maps but requires the user to perform a gesture when an estimation is needed. The resulting on-demand localization has advantages in terms of privacy and power efficiency. Initial experimental results, even under severe multipath conditions, show good accuracy in terms of angle of arrival estimation and promising results on localization.