Spacecraft Attitude Estimation with Unscented Kalman Filter Based on Maximum Correntropy Criterion

Abstract

Considering the presence of non-Gaussian environment in spacecraft attitude estimation missions and traditional nonlinear Kalman filter can not accurately solve this problem. This paper proposes an unscented Kalman filter (UKF) algorithm based on the maximum correntropy criterion (MCC). In the case of spacecraft equipped with gyroscope and star sensor, to describe the dynamic model of the spacecraft. Then the proposed algorithm, which called maximum correntropy unscented Kalman filter (MCUKF), and other traditional non-linear Kalman filter algorithm were applied to the corresponding scenario The results show that MCUKF has better estimation accuracy and filtering advantages for spacecraft attitude estimation than unscented Kalman filter in non-Gaussian environments.