Non linear optimum filter based smoothing Interacting Multiple Model for GPS navigation system

• Published in: 2012 International Conference on Recent Trends in Information Technology pp. 383 - 388
• Main Authors: Malleswaran, M., Vaidehi, V., Ramesh, H., Malin Bruntha, P.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2012
• Subjects: Estimation; Filtering algorithms; GPS; Interacting Multiple Model (IMM); Interacting Multiple Model Unscented Two Filter Smoother (IMM-UTFS); Navigation; Noise; Smoothing methods; Unscented Kalman Filter (UKF); Vehicle dynamics; Vehicles
• ISBN: 9781467315999; 1467315990
• DOI: 10.1109/ICRTIT.2012.6206794

An Interacting Multiple Model Unscented Two Filter Smoother (IMM-UTFS) approach for GPS navigation system is introduced in this paper. The Unscented Kalman Filter (UKF) propagates its state estimate and covariance through unscented transform without any need of linearization. The Interacting Multiple Model (IMM) algorithm obtains its estimate by combining the individual estimate from a number of parallel filters matched to different motion models of the vehicle. This paper adopts the Unscented Two Filter Smoother to the IMM algorithm to increase the navigation estimation accuracy. The dynamic behavior of the vehicle is analyzed and the simulation results show that IMM-UTFS can improve overall navigation accuracy as compared to traditional filters like UKF and multiple model filters like IMM-UKF.