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

AbstractIn 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) al...

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Veröffentlicht in:Journal of aerospace engineering 2022-09, Vol.35 (5)
Hauptverfasser: Qian, Huaming, Chu, Shuai, Zhao, Di
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Zhao, Di
description AbstractIn 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.
doi_str_mv 10.1061/(ASCE)AS.1943-5525.0001456
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source American Society of Civil Engineers:NESLI2:Journals:2014
subjects Algorithms
Computation
Entropy
Kalman filters
Numerical analysis
Random noise
Robustness (mathematics)
Technical Papers
title Adaptive Robust Minimum Error Entropy Unscented Kalman Filter for Satellite Attitude Estimation
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