文献类型：会议论文

英文题名：Extended Target Tracking for High Resolution Sensor Based Ensemble Kalman Filters

作者：Xu, Jiahe[1] Zhou, Yucheng[1] Jing, Yuanwei[2]

第一作者：徐佳鹤

通信作者：Xu, JH[1]

机构：[1]Chinese Acad Forestry, Inst Wood Ind, Dept Res, Beijing 100091, Peoples R China;[2]Northeastern Univ, Shenyang 110004, Peoples R China

会议论文集：22nd Chinese Control and Decision Conference

会议日期：MAY 26-AUG 28, 2010

会议地点：Xuzhou, PEOPLES R CHINA

语种：英文

外文关键词：extended target tracking; ensemble Kalman filter (EnKF); nonlinear filtering; uncertainty

年份：2010

摘要：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.