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Description
  • 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.
  • 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. (en)
Title
  • Unscented Kalman Filter: Aspects and Adaptive Setting of Scaling Parameter
  • Unscented Kalman Filter: Aspects and Adaptive Setting of Scaling Parameter (en)
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  • Unscented Kalman Filter: Aspects and Adaptive Setting of Scaling Parameter
  • Unscented Kalman Filter: Aspects and Adaptive Setting of Scaling Parameter (en)
skos:notation
  • RIV/49777513:23520/12:43915692!RIV13-GA0-23520___
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  • P(ED1.1.00/02.0090), P(GAP103/11/1353), S
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  • 9
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  • 176063
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  • RIV/49777513:23520/12:43915692
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  • stochastic systems; state estimation; nonlinear filters; Bayesian methods (en)
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  • US - Spojené státy americké
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  • [CFA3821687A5]
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  • IEEE Transactions on Automatic Control
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  • 57
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  • Straka, Ondřej
  • Šimandl, Miroslav
  • Duník, Jindřich
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  • 000308104700027
issn
  • 0018-9286
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  • 10.1109/TAC.2012.2188424
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  • 23520
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