文献类型：会议论文

英文题名：Sensor Fusion of Delay and Non-delay Signal using Unscented Kalman Filter with Moving Covariance

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：unscented Kalman filter (UKF); sensor fusion; delay signal; nonlinear system

年份：2010

摘要：This paper describes the design of unscented Kalman filter (UKF) to implement fusion of the delay and non-delay data for nonlinear discrete-time system in order to achieve the excellent dynamic response. We proposed a fusion method with UKF that only needs to update the stored covariance between two different time instants, instead of classical method, which is re-performing Kalman operation at every step from the time of measured delay signal to current time. To solve the fusion method, the measurement update equations of UKF algorithm is slightly modified in order to discuss and analysis the proposed fusion method clearly. With less computational cost comparing to the classical method and the uniformity of the computation in every iteration, the UKF is superior to extended Kalman filter (EKF) and offer much advantage in terms of estimation performance, which is verified by using MATLAB simulation on the high-update rate Wheel Mobile Robot (WMR).