Joint Estimation of Position and Channel Propagation Model Parameters in a Bluetooth Network

Wireless sensor networks are a promising solution for indoor location systems. However, many of these systems rely on algorithms that use parametric models of channel propagation where the parameters can be time variant. This paper introduces a new technique based on a Bayesian filtering method that estimates network node positions at the same time that propagation model parameters are extracted. Experimental results show the location estimation improvement of the proposed technique.