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

fYear

2009

fDate

9-12 Aug. 2009

Firstpage

401

Lastpage

405

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICMA.2009.5245091

Filename

5245091