期刊
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
卷 24, 期 1, 页码 365-371出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2015.2432155
关键词
Censored data; Kalman filtering; output nonlinearity; recursive estimation; Tobit model
资金
- U.S. Army Research Office [W911NF-10-1-0386]
Tobit model censored data arise in multiple engineering applications through saturating sensors, limit-of-detection effects, and image frame effects. In this brief, we introduce a novel formulation of the Kalman filter for Tobit Type 1 censored measurements. Our proposed formulation, called the Tobit Kalman filter, is identical to the standard Kalman filter in the no-censoring case. At or near the censored region, the Tobit Kalman filter utilizes a local approximation of the probability of censoring in order to provide a fully recursive estimate of the state and state error covariance. The additional computational burden of the method compared with the standard Kalman filter is limited to the calculation of m normal probability density functions and m normal cumulative density functions per update, where m is the number of measurements.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据