Abstract
The paper discusses choice for scaling parameter of the unscented transformation. By analyzing and comparing general method, the scaling parameter is selected as an optimization objective. Differential evolution algorithm is applied to the Unscented Kalman filter in offline model and online adaptive model. Experiment shows that the accuracy of UKF has been improved significantly by the two models.
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Jin, Y. (2012). Application of Differential Evolution to the Parameter Optimization of the Unscented Kalman Filter. In: Li, Z., Li, X., Liu, Y., Cai, Z. (eds) Computational Intelligence and Intelligent Systems. ISICA 2012. Communications in Computer and Information Science, vol 316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34289-9_38
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DOI: https://doi.org/10.1007/978-3-642-34289-9_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34288-2
Online ISBN: 978-3-642-34289-9
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