Adaptive Robust Minimum Error Entropy Unscented Kalman Filter for Satellite Attitude Estimation

Abstract

In recent years, the Kalman filter based on the minimum error entropy (MEE) criterion has been proposed, which outperforms the traditional Kalman filter in the presence of non-Gaussian noise. In practical applications, the estimated performance of the MEE unscented Kalman filter (MEE-UKF) algorithm is influenced by the kernel bandwidth (KB). In addition, it may be unstable in numerical computation. This paper proposes an adaptive robust MEE unscented Kalman filter (AMEE-UKF) to address the problem of instability in numerical computation. In addition, by setting an adaptive factor to optimize the MEE-UKF, an appropriate value of the KB can be obtained adaptively. The high accuracy and robustness of the AMEE-UKF were demonstrated by the simulation experiments.