Unbiased Minimum Variance Estimation for Discrete-Time Systems with Measurement Delay and Unknown Measurement Disturbance
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-25
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
This paper addresses the state estimation problem for stochastic systems with unknown measurement disturbances whose any prior information is unknown and measurement delay resulting from the inherent limited bandwidth.
For such complex systems, the Kalman-like one-step predictor independent of unknown measurement disturbances is designed based on the linear unbiased minimum variance criterion and the reorganized innovation analysis approach.
One simulation example shows the effectiveness of the proposed algorithms.
American Psychological Association (APA)
Guan, Yu& Song, Xinmin. 2018. Unbiased Minimum Variance Estimation for Discrete-Time Systems with Measurement Delay and Unknown Measurement Disturbance. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1206482
Modern Language Association (MLA)
Guan, Yu& Song, Xinmin. Unbiased Minimum Variance Estimation for Discrete-Time Systems with Measurement Delay and Unknown Measurement Disturbance. Mathematical Problems in Engineering No. 2018 (2018), pp.1-7.
https://search.emarefa.net/detail/BIM-1206482
American Medical Association (AMA)
Guan, Yu& Song, Xinmin. Unbiased Minimum Variance Estimation for Discrete-Time Systems with Measurement Delay and Unknown Measurement Disturbance. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1206482
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1206482