DocumentCode
1931615
Title
Notice of Retraction
Adaptive two-stage Kalman filter in the presence of random bias
Author
Hu Yi-ming ; Qin Yong-yuan
Author_Institution
Coll. of Autom., Northwestern Polytech. Univ. NWPU, Xi´an, China
Volume
6
fYear
2010
fDate
9-11 July 2010
Firstpage
135
Lastpage
138
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The two-stage Kalman filter requires the accurate information of unknown random bias. Unfortunately, this algebraic constraint is seldom satisfied for practical systems. The adaptive solution of estimating a set of dynamic state in the presence of a random bias employing a two-stage Kalman estimator is addressed. The solution performed well when the information of unknown random bias was inaccurate. The validity of the solution is verified with a simulative example.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The two-stage Kalman filter requires the accurate information of unknown random bias. Unfortunately, this algebraic constraint is seldom satisfied for practical systems. The adaptive solution of estimating a set of dynamic state in the presence of a random bias employing a two-stage Kalman estimator is addressed. The solution performed well when the information of unknown random bias was inaccurate. The validity of the solution is verified with a simulative example.
Keywords
adaptive Kalman filters; adaptive two-stage Kalman filter; algebraic constraint; dynamic state; random bias; two-stage Kalman estimator; Convergence; Equations; Two-stage Kalman estimation; adaptive Kalman filter; random bias;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5537-9
Type
conf
DOI
10.1109/ICCSIT.2010.5563730
Filename
5563730
Link To Document