Unscented Kalman Filter: Aspects and Adaptive Setting of Scaling Parameter

被引:105
作者
Dunik, Jindrich [1 ]
Simandl, Miroslav [1 ]
Straka, Ondrej [1 ]
机构
[1] Univ W Bohemia, Dept Cybernet, Fac Sci Appl, Plzen 30614, Czech Republic
关键词
Bayesian methods; nonlinear filters; state estimation; stochastic systems; NONLINEAR ESTIMATION; STATE ESTIMATION;
D O I
10.1109/TAC.2012.2188424
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 technical note deals with the unscented Kalman filter for state estimation of nonlinear stochastic dynamic systems with a special focus on the scaling parameter of the filter. Its standard choice is analyzed and its impact on the estimation quality is discussed. On the basis of the analysis, a novel method for adaptive setting of the parameter in the unscented Kalman filter is proposed. The results are illustrated in a numerical example.
引用
收藏
页码:2411 / 2416
页数:6
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