Bayesian Fusion of Asynchronous Inertial, Speed and Position Data for Object Tracking

Abstract

In this paper we present Bayesian methods for tracking scenarios in which an intrinsic coordinate model is considered and inertial mea- surements plus occasional position fixes are available. The methods are first tested using synthetic data, giving a comprehensive evalu- ation as to their performance. Further evaluation on real data also reveals our approaches can be favourable alternatives to existing in- ertial tracking/navigation models.