Title :
Study on adaptive filter with MEMS-INS/GPS integrated navigation system
Author :
Duan, Fengyang ; Yu, Huadong ; Li, Xiaolong
Author_Institution :
Electomechanical Eng. Coll., Changchun Univ. of Sci. & Technol., Changchun, China
Abstract :
The problem of conventional Kalman filter is that the model uncertainties will severly degrade the system performance. Because of that, the maximum likelihood estimator of innovation-based adaptive Kalman filter is studied in the paper. The improved algorithm is proposed in order to solve the limitation of ML adaptive estimator in the MEMS-INS/GPS integrated navigation system. The simulation results show that the improved algorithm is feasible and efficient.
Keywords :
Global Positioning System; adaptive Kalman filters; inertial navigation; micromechanical devices; Kalman filter; MEMS-INS/GPS Integrated Navigation system; inertial navigation system; innovation-based adaptive Kalman filter; integrated navigation system; maximum likelihood estimator; Adaptive filters; Filtering algorithms; Global Positioning System; Information filtering; Information filters; Maximum likelihood estimation; Radio navigation; Satellite broadcasting; Satellite navigation systems; State estimation; integrated navigation Kalman filter adaptive algorithm;
Conference_Titel :
Mechatronics and Automation, 2009. ICMA 2009. International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-2692-8
Electronic_ISBN :
978-1-4244-2693-5
DOI :
10.1109/ICMA.2009.5245091
