Robust Extended Kalman Filtering via Krein Space Estimation

A new robust extended Kalman filter is proposed for the discrete-time nonlinear systems with norm-bounded parameter uncertainties. After linearization of the nonlinear systems, the uncertainties described by the energy bounded constraint can be converted into an indefinite quadratic cost function to be minimized. The solution to the minimization problem is given by the extended Kalman filter derived in a Krein space, which leads to a robust version of the extended Kalman filter. Since the resulting robust filter has the same structure as a standard extended Kalman filter, the proposed filter can be readily designed by simply including the uncertainty terms in its formulas. The results of simulations are presented to demonstrate that the proposed filter achieves the robustness against parameter variation and performs better than the standard extended Kalman filter.