Robust Kalman filtering for discrete-time nonlinear systems with parameter uncertainties

This paper focuses on the robust Kalman filtering problem for discrete-time nonlinear systems with norm-bound parameter uncertainties. An explicit solution to the robust Kalman filtering problem is presented based on a Riccati equation approach. A new Riccati equation is derived in the presence of both the parameter uncertainties and the linearization errors. The proposed filter is illustrated by simulation on a pulsar positioning system (PPS) in comparison with the standard extended Kalman filter (EKF) and the robust H∞H∞ filter (RHF). To facilitate the application of the robust filter, a heuristic method is proposed to estimate the bounds of the model parameter uncertainties for the considered PPS.