An MM-based constrained Kalman filter for Student-t measurement noise outperforms VB, Laplace, and particle filter baselines in simulations, with a unified way to impose state constraints.
A variational Bayesian approach to robust sensor fusion based on Student-t distribution,
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Robust and Constrained Estimation of State-Space Models: A Majorization-Minimization Approach
An MM-based constrained Kalman filter for Student-t measurement noise outperforms VB, Laplace, and particle filter baselines in simulations, with a unified way to impose state constraints.