Maximum correntropy criterion variational Bayesian adaptive Kalman filter based on strong tracking with unknown noise covariances

DOI10.1016/j.jfranklin.2023.04.015zbMath1516.93271OpenAlexW4366169388MaRDI QIDQ6157358

Yunsheng Fan, Shuanghu Qiao, Guofeng Wang, Zhiping He, Dongdong Mu

Publication date: 21 June 2023

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2023.04.015

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Adaptive control/observation systems (93C40) Linear systems in control theory (93C05)

Cites Work

• Variational Bayesian adaptation of process noise covariance matrix in Kalman filtering
• A Novel Adaptive Kalman Filter With Inaccurate Process and Measurement Noise Covariance Matrices
• Correntropy: Properties and Applications in Non-Gaussian Signal Processing
• Approximate Inference in State-Space Models With Heavy-Tailed Noise
• An Adaptive Kalman Filter With Inaccurate Noise Covariances in the Presence of Outliers
• Robust Variational-Based Kalman Filter for Outlier Rejection With Correlated Measurements
• Design and application of nonlinear model‐based tracking control schemes employing DEKF estimation

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