Data Fusion for Hybrid and Autonomous Time-of-Flight Positioning

Abstract

Existing mobile devices such as smartphones rely on a multi-radio access technology (RAT) architecture to provide pervasive location information in various environmental contexts as the user is moving. Yet, existing architectures consider the different localization technologies as monolithic entities and choose the final navigation position from the RAT that is expected to provide the highest accuracy. In contrast, we propose to fuse timing range measurements of diverse radio technologies in order to circumvent the limitations of the individual radio access technologies. We take a first step in this direction and propose to fuse timing measurements of satellite navigation system and WiFi networks. We introduce different novel methods such as a data fuser, an estimator of WiFi ToF distance and a geometrical-statistical approach to best fuse the set of timing ranging measurements in presence of a rich set of measurements. Experimental results show that our solution allows the mobile device to efficiently self-position itself in diverse challenging scenarios.