A direct filter method for parameter estimation

JOURNAL OF COMPUTATIONAL PHYSICS

卷:398

Article

Archibald, Richard¹  Bao, Feng²  Tu, Xuemin³ 

[1] Oak Ridge Natl Lab, Comp Sci & Computat Sci, Oak Ridge, TN USA

[2] Florida State Univ, Dept Math, Tallahassee, FL 32306 USA

[3] Univ Kansas, Dept Math, Lawrence, KS 66045 USA

关键词: Parameter estimation;    State-space model;    Data assimilation;    Nonlinear filtering problem;    Bayesian inference;   

DOI  :  10.1016/j.jcp.2019.108871

来源: Elsevier

【 摘 要 】

Parameter estimation is an important research topic in data assimilation. In this paper, a novel parameter estimation method is introduced, where the parameter is considered as the state process in a nonlinear filtering problem and the state model that contains the parameter is used to construct a pseudo-observation. This approach is named the direct filter method since nonlinear filtering algorithms are used to estimate the parameter directly without estimating the state model as part of the solution in the nonlinear filtering problem. Numerical experiments are carried out to examine the effectiveness and accuracy of the direct filter method. (C) 2019 Elsevier Inc. All rights reserved.

【 授权许可】

Free