2020 IEEE 23rd International Conference on Information Fusion (FUSION) 2020
DOI: 10.23919/fusion45008.2020.9190507
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Outlier-Robust Schmidt-Kalman Filter Using Variational Inference

Abstract: The Schmidt-Kalman filter (SKF) achieves filtering consistency in the presence of biases in system dynamic and measurement models through accounting for their impacts when updating the state estimate and covariance. However, the performance of the SKF may break down when the measurements are subject to non-Gaussian and heavy-tail noise. To address this, we impose the Wishart prior distribution on the precision matrix of measurement noise, such that the measurement likelihood now has heavier tails than the Gaus… Show more

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References 34 publications
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