Title :
Extended target tracking for high resolution sensor based ensemble Kalman filters
Author :
Xu, Jiahe ; Zhou, Yucheng ; Jing, Yuanwei
Author_Institution :
Dept. of Res. Inst. of Wood Ind., Chinese Acad. of Forestry, Beijing, China
Abstract :
The ensemble Kalman filter (EnKF) is developed to extended target tracking problem for high resolution sensors. The ensemble Kalman filter is based on an ellipsoidal model, which is proposed to exploit sensor measurement of target extent. The ellipsoidal model can provide extra information to enhance tracking accuracy, data association performance, and target identification. In contrast to the most commonly used extended Kalman filter (EKF), the EnKF provide more accurate and reliable estimation performance, due to the presence of high nonlinearity of the model. Correspondingly, the EnKF has lower computational complexity than the EKF. The EnKF is sensitive to uncertainty in the dynamic model, but much of the lost performance can be restored by treating the uncertainty as a random disturbance input. The developed EnKF algorithm on extended target tracking problem is validated and evaluated by computer simulations.
Keywords :
Kalman filters; sensors; target tracking; computational complexity; dynamic model; ellipsoidal model; ensemble Kalman filters; extended target tracking; high resolution sensor; sensor measurement; target identification; Filtering; Forestry; Infrared sensors; Kinematics; Radar tracking; Shape measurement; Spaceborne radar; State estimation; Target tracking; Uncertainty; ensemble Kalman filter (EnKF); extended target tracking; nonlinear filtering; uncertainty;
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
DOI :
10.1109/CCDC.2010.5498595