KALMAN FILTERING APPROXIMATIONS IN TRIPLET MARKOV GAUSSIAN SWITCHING MODELS

被引:0
|
作者
Abbassi, Noufel [1 ]
Benboudjema, Dalila [2 ]
Pieczynski, Wojciech [1 ]
机构
[1] Telecom Sudparis, Inst Telecom, CNRS, Dept CITI,UMR 5157, 9 Rue Charles Fourier, F-91000 Evry, France
[2] Univ Cergy Pontoise, CNRS, ENSEA, Equipe ETIS, Cergy Pontoise F-95000, France
关键词
Gaussian switching system; exact Kalman filtering; particle filter;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We consider a general triplet Markov Gaussian linear system (X,R,Y), where X is hidden continuous, R is hidden discrete, and Y is observed continuous. Exact Kalman filter (KF) is not workable and two approximations are considered in the paper. The classical one consists of particle filtering, which is a new extension of the classical method we propose. Another new method we propose consists of replacing the model by a simpler one, in which (R,Y) is Markovian and in which exact KF can be performed. We show the interest of our method via experiments.
引用
收藏
页码:77 / 80
页数:4
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