Title :
Extended Set Membership State Estimation Algorithm for Land Vehicle Navigation System
Author :
He, Qing ; Tan, Shuai ; Wanshan, Dai
Author_Institution :
Sch. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
Abstract :
In this paper, the Extended Set Membership (ESM) based on out-bounding ellipsoidal algorithm is used as a means of improving the performance of land vehicle position accuracy. Contrary to classical Extended Kalman Filtering (EKF), this approach provides guaranteed result in the sense that a set is computed that contains all of the feasible state that are consistent with the data and hypotheses. Simulation results are given to show that the ESM is superior to the EKF in state estimation of land vehicle navigation system.
Keywords :
Kalman filters; navigation; position control; state estimation; extended Kalman filtering; extended set membership state estimation algorithm; land vehicle navigation system; land vehicle position accuracy; out bounding ellipsoidal algorithm; Ellipsoids; Filtering; Gaussian noise; Kalman filters; Land vehicles; Navigation; Noise measurement; State estimation; Stochastic resonance; Stochastic systems; Extended Set Membership; Navigation; Nonlinear Ssystem; State Estimation;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
DOI :
10.1109/ICMTMA.2010.299