文献类型：会议论文

英文题名：The Unscented Kalman Filtering in Extended Noise Environments

作者：Zhou, Yucheng[1] Xu, Jiahe[2] Jing, Yuanwei[] Dimirovski, Georgi M.[3,4]

第一作者：周玉成

通信作者：Zhou, YC[1]

机构：[1]Chinese Acad Forestry, Inst Wood Ind, Dept Res, Fac Engn, Beijing 100091, Peoples R China;[2]Northeastern Univ, Fac Informat Sci & Engn, Shenyang 110004, Peoples R China;[3]Dogus Univ, Fac Engn, TR-34722 Istanbul, Turkey;[4]SS Cyril & Methodius Univ, Fac FEIT, MK-1000 Skopje, North Macedonia

会议论文集：American Control Conference 2009

会议日期：JUN 10-12, 2009

会议地点：St Louis, MO

语种：英文

外文关键词：Additive noise - Intelligent systems - Monte Carlo methods

年份：2009

摘要：This paper introduces an extended environment for the unscented Kalman filtering that considers also the presence of additive noise on input observations in order to solve the problem of optimal estimation of noise-corrupted input and output sequences. This environment includes as sub-cases both errors-in-variables filtering and unscented Kalman filtering. The unscented Kalman flitering to the presence of additive noise on input observations is considered, and is used to solve the problem of optimal estimation of noise-corrupted input and output sequences. A Monte Carlo simulation shows that the performance of the unscented Kalman filtering technique leads to the expected minimal variance estimates.