A Robust Kalman Filter for Heavy-Tailed Measurement Noise Based on Gamma Pearson VII Mixture Distribution

A Robust Kalman Filter for Heavy-Tailed Measurement Noise Based on Gamma Pearson VII Mixture Distribution

This study develops an enhanced state estimation framework by integrating the Kalman filtering mechanism with a Gamma Pearson VII (GaPV) hybrid probability model to address non-stationary heavy-tailed noise characteristics in measurement systems. This innovative methodology synthesizes Gaussian morp...

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Bibliographic Details
Main Authors: Shen Liang, Guoliang Xu, Zhenmei Qin
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Gamma Pearson VII distribution
Kalman filter
variational Bayes
non-stationary heavy-tailed noise
Online Access:https://ieeexplore.ieee.org/document/10925424/
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https://ieeexplore.ieee.org/document/10925424/

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