DocumentCode :
87612
Title :
Linear minimum mean squared estimation of measurement bias driven by structured unknown inputs
Author :
Lin Zhou ; Yan Liang ; Jie Zhou ; Feng Yang ; Quan Pan
Author_Institution :
Sch. of Autom., Northwestern Polytech. Univ., Xi´an, China
Volume :
8
Issue :
8
fYear :
2014
fDate :
Oct-14
Firstpage :
977
Lastpage :
986
Abstract :
In this study, a generalised systematic bias (SB) is presented, which is represented via a dynamic model driven by structured unknown inputs (UI). The online SB estimation is implemented in two steps. In the first step, the state-free SB measurement and the UI-free SB dynamic model are derived in the case that UI-free condition holds. In the second step, the linear minimum mean squared filter is obtained via orthogonal principle, and the sufficient condition of filtering stability is presented. A simulation about target tracking is given to verify the proposed method.
Keywords :
filtering theory; mean square error methods; UI-free SB dynamic model; filtering stability; generalised systematic bias; linear minimum mean squared estimation; mean squared filter; online SB estimation; orthogonal principle; state-free SB measurement; structured unknown inputs;
fLanguage :
English
Journal_Title :
Radar, Sonar & Navigation, IET
Publisher :
iet
ISSN :
1751-8784
Type :
jour
DOI :
10.1049/iet-rsn.2013.0311
Filename :
6911077
Link To Document :
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