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—The two-stage Unscented Kalman Filter (TUKF) is proposed to consider the nonlinear system in the presence of unknown random bias in a number of practical situations. The adaptive fading UKF is designed by using the forgetting factor to compensate the effects of incomplete information. The TUKF to estimate unknown random bias is designed by using the(More)
This paper describes the design of ensemble Kalman filter (EnKF) to implement fusion of the delay and non-delay data for nonlinear discrete-time system in order to achieve the excellent dynamic response. We proposed a fusion method with EnKF that only needs to update the stored covariance between two different time instants, instead of classical method,(More)
—This paper introduces an extended environment for the unscented Kalman filtering that considers also the presence of additive noise on input observations in order to solve the problem of optimal estimation of noise-corrupted input and output sequences. This environment includes as sub-cases both errors-in-variables filtering and unscented Kalman filtering.(More)
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