Self-assessment of Local Filters by Non-Gaussianity Measures

被引：0
|
作者：
Dunik, Jindrich [1 ]
Straka, Ondrej [1 ]
Simandl, Miroslav [1 ]
机构：
[1] Univ W Bohemia, Fac Sci Appl, Dept Cybernet, Res Ctr New Technol Informat Soc, Plzen, Czech Republic
来源：
2014 AMERICAN CONTROL CONFERENCE (ACC) | 2014年
关键词：
state estimation; nonlinear filters; Kalman filtering; non-Gaussianity measures; nonlinearity measures; KALMAN FILTER;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper deals with state estimation of stochastic nonlinear systems by means of local filters. A new technique is designed to provide a self-assessment of the filter with respect to its estimate quality. It uses a non-Gaussianity measure based on conditional third moment of the state to indicate a possible decrease of estimate quality. The technique is proposed for general local filters with detailed specification for three selected filters in the Kalman filtering framework. An application of the technique is illustrated in a numerical example.
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页数：6
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