Robust extended Kalman filtering for nonlinear systems with multiplicative noises

By X. Kai, Liangdong Liu, Liu Yiwu. 2011

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Quantised recursive filtering for a class of nonlinear systems with multiplicative noises and missing measurements (2013, methodology): “Based on Xiong et al. (2011) and in view of Lemmas 2 and 5, the filter parameter is designed such that an optimised upper bound for the filtering error covariance is achieved at each sampling instant.”
Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements (2012, methodology): “Along this direction, many alternative filtering schemes have been reported in the literature including theH∞ filtering [15,21,27,30,36],mixedH2/H∞ filtering [20, 29], set-value estimation [1, 5, 6, 18] and robust extended Kalman filter (EKF) design [11,12,31,32].”