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.