DocumentCode
1637518
Title
A Novel Unscented Kalman Filter in Autonomous Optical Navigation
Author
Shulin, Sui ; Wenlong, Yao ; Lihong, Sun ; Jian, Yuan
Author_Institution
Qingdao Univ. of Sci. & Technol., Qingdao
fYear
2007
Firstpage
462
Lastpage
466
Abstract
Through much research on unscented Kalman filter based on scaled and square-root algorithm in autonomous navigation, it is known that these algorithms take so much time on calculation. So an improved unscented Kalman filter algorithm is proposed in the paper for autonomous navigation to solve the non-real-time difficulty. Simple scheme is adopted to predigest the choose procedure of sigma-points and weights, which reduces a mass of complex operations. From both theory and practical simulation, it is shown that much mass of calculation is reduced when the dimension of state matrix is large, and not leads to bad filtering performance.
Keywords
Kalman filters; matrix algebra; navigation; autonomous optical navigation; filtering performance; scaled algorithm; square-root algorithm; state matrix; unscented Kalman filter; Covariance matrix; Extraterrestrial measurements; Filtering; Gaussian distribution; Navigation; Noise measurement; Nonlinear equations; Optical control; Optical filters; State estimation; Autonomous optical navigation; SR-UKF; UKF;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference, 2007. CCC 2007. Chinese
Conference_Location
Hunan
Print_ISBN
978-7-81124-055-9
Electronic_ISBN
978-7-900719-22-5
Type
conf
DOI
10.1109/CHICC.2006.4346767
Filename
4346767
Link To Document