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Truncated Unscented Particle Filter

Citace: [] STRAKA, O., DUNÍK, J., ŠIMANDL, M. Truncated Unscented Particle Filter. In Proceedings of the 2011 American Control Conference. San Francisco, USA: AACC, 2011. s. 1825-1830. ISBN: 978-1-4577-0081-1 , ISSN: 0743-1619
Jazyk publikace: eng
Anglický název: Truncated Unscented Particle Filter
Rok vydání: 2011
Místo konání: San Francisco, USA
Název zdroje: AACC
Autoři: Ing. Ondřej Straka Ph.D. , Ing. Jindřich Duník Ph.D. , Prof. Ing. Miroslav Šimandl CSc.
Abstrakt EN: The problem of state estimation of nonlinear stochastic dynamic systems with nonlinear inequality constraints is treated. The paper focuses on a particle filtering approach, which provides an estimate of the state in the form of a probability density function. A new computationally efficient particle filter for the constrained estimation problem is proposed. The importance function of the particle filter is generated by the unscented Kalman filter that is supplemented with a designed truncation technique to accommodate the constraint. The proposed filter is illustrated in a numerical example.
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