DocumentCode :
466546
Title :
INS/GPS Integrated Navigation Uncertain System State Estimation Based on Minimal Variance Robust Filtering
Author :
Zhou Wu ; Shi, Hang ; Liu, Baosheng
Author_Institution :
Sch. of Mechatronical Eng. & Autom., National Univ. of Defense Technol., Changsha
Volume :
1
fYear :
2006
fDate :
4-6 Oct. 2006
Firstpage :
631
Lastpage :
634
Abstract :
INS/GPS integrated navigation systems are used for positioning and attitude determination in a wide range of applications. Combining INS and GPS organically, we can get an integrated navigating system which can overcome the respective defects of the two systems and develop their advantages to form a complementary structure at the same time. GPS measurements can be used correct the INS and sensor errors to provide high accuracy real-time navigation (Farrell, 1998). The integration of GPS and INS measurements is usually achieved using a Kalman filter. But, usually uncertainties exist in INS/GPS integrated real systems, which may cause filtering to divergence for classical Kalman filter. In order to solve this problem, a robust filter with minimal variance is addressed by this paper
Keywords :
Global Positioning System; Kalman filters; inertial navigation; state estimation; uncertain systems; Kalman filter; attitude determination; global positioning system; inertial navigation systems; integrated navigation uncertain system; minimal variance robust filtering; positioning determination; state estimation; Application software; Automation; Filtering; Global Positioning System; Navigation; Position measurement; Robustness; State estimation; Systems engineering and theory; Uncertain systems; Integrated Navigation; Kalman Filter; Minimal Variance Robust Filterin[SHI,01]; uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Engineering in Systems Applications, IMACS Multiconference on
Conference_Location :
Beijing
Print_ISBN :
7-302-13922-9
Electronic_ISBN :
7-900718-14-1
Type :
conf
DOI :
10.1109/CESA.2006.4281729
Filename :
4281729
Link To Document :
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