This article presents a Kalman-type recursive estimator for discrete-time systems with a measurement noise modeled by a Gaussian-uniform mixture. The objective is to deal with data containing outliers that degrade the performance of the regular Kalman filter. The proposed non-Gaussian noise model takes into account the reliability of the measurement with respect to erroneous data. The Kalman-type estimator is based on Masreliez's formulation which copes with non-Gaussian noise models. Results in different simulated conditions are displayed to evaluate the performance of the newly-presented algorithm and to compare it to state-of-art alternatives.
A Gaussian Uniform Mixture Model for Robust Kalman Filtering
IEEE Transactions on Aerospace and Electronic Systems ; 56 , 4 ; 2656-2665
2020-08-01
1719688 byte
Article (Journal)
Electronic Resource
English
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