Unscented Kalman Filtering for spacecraft attitude state and parameter estimation

Abstract

An Unscented Kalman Filter (UKF) is derived in an attempt to solve the spacecraft dual estimation problem with greater accuracy than is attainable with an Extended Kalman Filter (EKF). The EKF is an extension of the linear Kalman Filter for nonlinear systems. Although the EKF has been used successfully in many nonlinear applications, the performance is limited, due mostly to the truncation of all but first-order terms. The UKF is able to achieve greater estimation performance than the EKF through the use of the unscented transformation (UT). The UT allows the UKF to capture first and second order terms of the nonlinear system.