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Comments on “Performance evaluation of UKF-based nonlinear filtering”. (English) Zbl 1137.93417

Summary: This note points out that the main result of the paper [K. Xiong, H. Y. Zhang and C. W. Chan, Automatica 42, No. 2, 261–270 (2006; Zbl 1103.93045)] can be extended to a class of so-called Gaussian filters. It justifies a practical countermeasure of the divergence, i.e., adding small quantities to the noise covariance matrix to stabilize the filter.

MSC:

93E11 Filtering in stochastic control theory
93E15 Stochastic stability in control theory
93C55 Discrete-time control/observation systems

Citations:

Zbl 1103.93045
Full Text: DOI

References:

[1] Boutayeb, M.; Aubry, D., A strong tracking extended Kalman observer for nonlinear discrete-time systems, IEEE Transactions on Automatic Control, 44, 8, 1550-1556 (1999) · Zbl 0957.93086
[2] Boutayeb, M.; Rafaralahy, H.; Darouach, M., Convergence analysis of the extended Kalman filter used as observer for nonlinear deterministic discrete-time systems, IEEE Transactions on Automatic Control, 42, 4, 581-586 (1997) · Zbl 0876.93089
[3] Brown, R. G., Introduction to random signal analysis and Kalman filtering (1983), Wiley: Wiley New York
[4] Ito, K.; Xiong, K. Q., Gaussian filters for nonlinear filtering problems, IEEE Transactions on Automatic Control, 45, 5, 910-927 (2000) · Zbl 0976.93079
[5] Norgaard, M.; Poulsen, N. K.; Ravn, O., New developments in state estimation for nonlinear systems, Automatica, 36, 11, 1627-1638 (2000) · Zbl 0973.93050
[6] Wu, Y.; Hu, D.; Wu, M.; Hu, X., A numerical-integration perspective on Gaussian filters, IEEE Transactions on Signal Processing, 56, 8, 2910-2921 (2006) · Zbl 1388.65025
[7] Xiong, K.; Zhang, H. Y.; Chan, C. W., Performance evaluation of UKF-based nonlinear filtering, Automatica, 42, 2, 261-270 (2006) · Zbl 1103.93045
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