A Robust Unscented Kalman Filter for Nonlinear Dynamical Systems with Colored Noise

Abstract

The Unscented Kalman filter (UKF) is the commonest filter for state estimation of a discrete-time nonlinear system corrupted with noise. If the process noise and measurement noise of nonlinear system are Gaussian and white, the UKF filter will be optimal. While the process or measurement noises are colored noise, the UKF filter will be instead suboptimal. In this paper, a robust UKF (R-UKF) filter is proposed in order to solve this problem. The proposed filter allows that the conventional UKF is applied for discrete-time nonlinear system corrupted with colored noise. Simulation results show that the R-UKF has better performance in estimation of the corrupted state of dynamical system by colored noise in comparison with those of using conventional UKF algorithm. 