The unscented Kalman filtering in extended noise environments
ACC'09 Proceedings of the 2009 conference on American Control Conference
Performance evaluation of UKF-based nonlinear filtering
Automatica (Journal of IFAC)
Robust control on saturated Markov jump systems with missing information
Information Sciences: an International Journal
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In this paper, the stochastic stability of the discrete-time unscented Kalman filter for general nonlinear stochastic systems with intermittent observations is proposed. It is shown that the estimation error remains bounded if the system satisfies some assumptions. And the statistical convergence property of the estimation error covariance is studied, showing the existence of a critical value for the arrival rate of the observations. An upper bound on this expected state error covariance is given. A numerical example is given to illustrate the effectiveness of the techniques developed.