DocumentCode
539085
Title
Estimation and filtering of Gaussian variables with linear inequality constraints
Author
Linfeng Xu ; Li, X. Rong
Author_Institution
Sch. of Electron. & Inf. Eng., Xian Jiaotong Univ., Xi´an, China
fYear
2010
fDate
26-29 July 2010
Firstpage
1
Lastpage
6
Abstract
In practice, a parameter or the state of a system is often subject to constraints. This paper considers the estimation problem for the parameter or the state constrained by a class of linear inequalities. Two sequential methods for optimal parameter estimation in the MMSE sense are obtained. They have an analytic form, which is different from most existing methods. For a dynamic system with constrained state, we model it with density function and provide a suboptimal filter based on reasonable approximations. This filter is applied to an example of tracking a ground moving target and its performance is also examined.
Keywords
Gaussian processes; filtering theory; mean square error methods; parameter estimation; Gaussian variable; MMSE; constrained state; density function; dynamic system; filtering; linear inequality constraint; optimal parameter estimation; suboptimal filter; Approximation methods; Bayesian methods; Estimation; Kalman filters; Noise measurement; Roads; Target tracking; Inequality constraint; filtering; optimal estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion (FUSION), 2010 13th Conference on
Conference_Location
Edinburgh
Print_ISBN
978-0-9824438-1-1
Type
conf
DOI
10.1109/ICIF.2010.5711866
Filename
5711866
Link To Document