DocumentCode
2821069
Title
Adaptive Extended Kalman Filtering for SINS/GPS Integrated Navigation Systems
Author
Hao, Yanling ; Guo, Zhen ; Sun, Feng ; Gao, Wei
Author_Institution
Coll. of Autom., Harbin Eng. Univ., Harbin, China
Volume
2
fYear
2009
fDate
24-26 April 2009
Firstpage
192
Lastpage
194
Abstract
An improved adaptive extended Kalman filtering algorithm is proposed here to estimate the measurement noise on-line for the SINS/GPS integrated navigation systems. The measurement remnant chi-square method is used to automatically adjust the sliding window basing on the innovation sequence. The experiment result shows that this new approach could improve the accuracy of the integrated navigation system effectively when the measurement noise is unknown.
Keywords
Global Positioning System; adaptive Kalman filters; inertial navigation; SINS-GPS integrated navigation system; adaptive extended Kalman filtering algorithm; innovation sequence; measurement remnant chi-square method; online measurement noise estimation; sliding window; Adaptive filters; Filtering; Global Positioning System; Kalman filters; Navigation; Noise measurement; Silicon compounds; Technological innovation; Velocity measurement; Working environment noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location
Sanya, Hainan
Print_ISBN
978-0-7695-3605-7
Type
conf
DOI
10.1109/CSO.2009.429
Filename
5193929
Link To Document