Maximum correntropy unscented Kalman and information filters for non-Gaussian measurement noise

DOI10.1016/j.jfranklin.2017.10.023zbMath1380.93260OpenAlexW2770746583MaRDI QIDQ682740

Guoqing Wang, Ning Li, Yong-Gang Zhang

Publication date: 5 February 2018

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

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2017.10.023

zbMATH Keywords

nonlinear systemsstate estimation problemkernel bandwidthlarge outliersmaximum correntropy unscented Kalman and information filtersnon-Gaussian measurement noiseweighted least square method

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10)

Related Items (14)

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Cites Work

• Maximum correntropy Kalman filter
• High-degree cubature Kalman filter
• Stochastic stability of the discrete-time extended Kalman filter
• Gaussian filters for nonlinear filtering problems
• Correntropy: Properties and Applications in Non-Gaussian Signal Processing
• Generalized correlation function: definition, properties, and application to blind equalization
• Cubature Kalman Filters
• Stochastic Stability of the Extended Kalman Filter With Intermittent Observations
• Maximum correntropy unscented filter
• Nonlinear Bayesian estimation using Gaussian sum approximations
• New developments in state estimation for nonlinear systems

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