Research
Research Divisions
Research Progress
Achievements
Research Programs
Location: Home>Research>Research Progress
A Novel Case of Practical Exponential Observer Using Extended Kalman Filter
Author: Update times: 2018-12-19                          | Print | Close | Text Size: A A A

This technical note presents a case of practical exponential observer using extended Kalman filter (EKF) independent of certain restrictions, such as online check and estimation error of initial state. Recursive state estimation is usually a challenge for discrete-time nonlinear system in terms of computation cost. EKF is attractive with its simplicity since it is considered as an exponential observer given the above restrictions. However, those restrictions are so mathematically complicated that EKF cannot be practical in estimation. A novel case for an exponential observer using EKF is proposed, which is independent of such restrictions. However, these restrictions are proved to be unnecessary in the case. The proposed case is illustrated by a navigation system scenario. The validity of the case is demonstrated by a numerical simulation experiment. The system is deterministic.

This work was published on IEEE ACCESS,2018,6:58004-58011.titled A Novel Case of Practical Exponential Observer Using Extended Kalman Filter.

Copyright © 2003 - 2013. Shenyang Institute of Automation (SIA), Chinese Academy of Sciences
All rights reserved. Reproduction in whole or in part without permission is prohibited.
Phone: 86 24 23970012 Email: siamaster@sia.cn