Robust Kalman filtering for nonlinear systems with parameter uncertainties

This paper addresses state estimation problems for nonlinear systems with parameter uncertainties. A new robust unscented Kalman filter is devised by analyzing the influence which parameter uncertainties give to covariance matrix. Proposed method is one form of the DKF, but proposed method have a merit that designing weight matrix is easier than DKF in a certain situation. The validity of the proposed method is illustrated in Monte Carlo simulation.