Extended Target Tracking for High Resolution Sensor Based Ensemble Kalman Filters
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.
extended target tracking ensemble Kalman filter (EnKF) nonlinear filtering uncertainty
Jiahe Xu Yucheng Zhou Yuanwei Jing
Department of Research Institute of Wood Industry Chinese Academy of Forestry, Beijing, 100091 Information Science and Engineering, Northeastern University, 110004, Shenyang, Liaoning
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
3308-3313
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）