Extended Target Tracking using an IMM Based Rao-Blackwellised Unscented Kalman Filter

摘要：

An extended target tracking problem for high resolution sensors is considered.An ellipsoidal model is proposed to exploit sensor measurement of target extent,which can provide extra information to enhance tracking accuracy,data association performance,and target identification.Due to the presence of high nonlinearity of the model,a Rao-Blackwellised unscented Kalman filter (RBUKF) is adopted in this paper.In contrast to the most commonly used extended Kalman filter (EKF),the RBUKF provides more accurate and reliable estimation performance,without increasing any computational complexity.An interacting multiple model (IMM) technique is combined with the RBUKF method to adapt the target maneuver and motion mode switching problem which is vital for nonlinear filtering.The developed IMM-RBUKF algorithm on extended target tracking problem is validated and evaluated by computer simulations.

关键词： extended target tracking nonlinear filtering unscented Kalman filter Rao-Blackwellised Kalman filter

作者: Zhiwen Zhong Huadong Meng Xiqin Wang

作者单位: Department of Electronic Engineering,Tsinghua University,Beijing 100084,P.R.China

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）