Rotated Unscented Kalman Filter for Two State Nonlinear Systems

Abstract

In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) have<br />became basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.<br />The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yield<br />with UKF for the most nonlinear systems. In this paper, we use a new approach for a two variable<br />state nonlinear systems which it is called Rotated UKF (R_UKF). R_UKF can be reduced estimation<br />error and reached for least error in state estimation.