Probabilistic Methods for Location Estimation in Wireless Networks

Abstract

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.