Correspondence: Author's reply to "Comments on 'Performance evaluation of UKF-based nonlinear filtering"'

Authors:
K. Xiong;H. Y. Zhang;C. W. Chan
Affiliations:
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China;School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China;Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
Venue:
Automatica (Journal of IFAC)
Year:
2007

Citing 2
Cited 2

Correspondence: Comments on "Performance evaluation of UKF-based nonlinear filtering"

Automatica (Journal of IFAC)
Performance evaluation of UKF-based nonlinear filtering

Automatica (Journal of IFAC)

A Gaussian approximation recursive filter for nonlinear systems with correlated noises

Automatica (Journal of IFAC)
TDOA-based adaptive sensing in multi-agent cooperative target tracking

Signal Processing

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Abstract

It is stated in the above-mentioned comment that the main result of the paper Xiong, Zhang, et al. [(2006). Performance evaluation of UKF-based nonlinear filtering. Automatica 42(2), 261-270] can be extended to a class of filters, such as the extended Kalman filter (EKF). As we show here, this belief can be justified in a rigorous way, even for the nonlinear stochastic system with a nonlinear measurement equation.