Two-stage Unscented Kalman Filter for nonlinear systems in the presence of unknown random bias

Abstract

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 adaptive fading UKF. This filter can be used for nonlinear systems with unknown random bias on the assumption that the stochastic information of a random bias is incomplete. The stability of the TUKF is analyzed and ensured under certain conditions. The performance of the TUKF is verified by using MATLAB simulation on the high-update rate Wheel Mobile Robot (WMR).