IMM-EKF based Road Vehicle Navigation with Low Cost GPS/INS

Actual solutions for the road vehicle navigation problem point to the combination of GPS, odometry and inertial sensors. To combine the information coming from these sensors, most of actual researchers rely on the implementation of variations of the Kalman filter (KF) and the extended Kalman filter (EKF) for non-linear systems. Despite the fact that, in these filters, the definition of the proper vehicle model is of extreme importance, there is not a unique common filter suitable for all the usual situations in which a road vehicle is involved. The diversity of possible maneuvers and the need of realistic noise considerations adjusted to each driving situation encourage the application of IMM (interactive multi-model) techniques in the road navigation. Traditionally applied to the aerial sector, IMM based methods run different models at the same time, selecting that one which better represents the system behavior anytime. For road vehicles, the IMM-EKF solution presented in this paper allows the exploitation of highly dynamic models just when required, avoiding the impoverishment of the solution due to unrealistic noise considerations during straight or mild trajectories. Selected results presented in this paper confirm the improvements obtained by using the IMM-EKF developed, as compared with the single model solution