Kimmo Valtonen

Topics in probabilistic location estimation in wireless networks

In this survey-style paper we demonstrate the usefulness of the probabilistic modelling framework in solving not only the actual positioning problem, but also many related problems involving issues like calibration, active learning, error estimation and tracking with history. We also point out some interesting links between positioning research done in the area of robotics and in the area of wireless radio networks.

Probabilistic Methods for Location Estimation in Wireless Networks

Probabilistic modeling techniques offer a unifying theoretical framework for solving the problems encountered when developing location-aware and location-sensitive applications in wireless radio networks. In this paper we demonstrate the usefulness of the probabilistic modelling framework in solving not only the actual location estimation (positioning) problem, but also many related problems involving pragmatically important issues like calibration, active learning, error estimation and tracking with history. Some interesting links between positioning research done in the area of robotics and in the area of wireless radio networks are also discussed.