Smoothed State Estimation via Efficient Solution of Linear Equations

被引:3
|
作者
Geng, Li-Hui [1 ]
Wills, Adrian George [2 ]
Ninness, Brett [3 ]
Schon, Thomas Bo [4 ]
机构
[1] Tianjin Univ Technol & Educ, Sch Automation & Elect Engn, Tianjin Key Lab Informat Sensing & Intelligent Con, Tianjin 300222, Peoples R China
[2] Univ Newcastle, Sch Engn, Callaghan, NSW 2308, Australia
[3] Univ Newcastle, Fac Engn & Built Environm, Callaghan, NSW 2308, Australia
[4] Uppsala Univ, Dept Informat Technol, Div Syst & Control, Uppsala 75105, Sweden
基金
瑞典研究理事会;
关键词
Efficient smoothing algorithm; fixed-interval smoothing; linear stochastic system; smoothed state estimation;
D O I
10.1109/TAC.2022.3230368
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article addresses the problem of computing fixed-interval smoothed state estimates of a linear time-varying Gaussian stochastic system. There already exist many algorithms that perform this computation, but all of them impose certain restrictions on system matrices in order for them to be applicable, and the restrictions vary considerably between the various existing algorithms. This article establishes a new sufficient condition for the fixed-interval smoothing density to exist in a Gaussian form that can be completely characterized by associated means and covariances. It then develops an algorithm to compute these means and covariances with no further assumptions required. This results in an algorithm more generally applicable than any one of the multitude of existing algorithms available to date.
引用
收藏
页码:5877 / 5889
页数:13
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