DocumentCode
2867730
Title
The Unscented Kalman Filter for State Estimation of 3-Dimension Bearing-Only Tracking
Author
Wang Wan-ping ; Liao Sheng ; Xing Ting-wen
Author_Institution
Inst. of Opt. & Electron., Chinese Acad. of Sci., Chengdu, China
fYear
2009
fDate
19-20 Dec. 2009
Firstpage
1
Lastpage
5
Abstract
The unscented Kalman filter (UKF) is presented as an alternative of extend Kalman filter (EKF) for bearing-only tracking. Compared with EKF, UKF has a better performance that estimation precision does not depend on state initialization error. In the same noise angle measurement data, UKF has better precision. UKF can be used to have a good estimation at large state initialization error. Simulation experiments are present and show that UKF is used for better state estimation result in 3-dimension bearing-only tracking.
Keywords
Kalman filters; nonlinear filters; state estimation; tracking; 3-dimension bearing-only tracking; extend Kalman filter; noise angle measurement; state estimation; state initialization error; unscented Kalman filter; Goniometers; Noise measurement; Nonlinear optics; Nonlinear systems; Optical filters; Radar tracking; Random variables; Recursive estimation; State estimation; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4994-1
Type
conf
DOI
10.1109/ICIECS.2009.5366448
Filename
5366448
Link To Document