A Novel Robust Student's t-Based Kalman Filter
A novel robust Student's t-based Kalman filter is proposed by using the variational Bayesian
approach, which provides a Gaussian approximation to the posterior distribution. Simulation …
approach, which provides a Gaussian approximation to the posterior distribution. Simulation …
A type-3 logic fuzzy system: Optimized by a correntropy based Kalman filter with adaptive fuzzy kernel size
In this study, a self-organizing interval type-3 fuzzy logic system (SO-IT3FLS) with a new
learning algorithm is presented. An adaptive kernel size using fuzzy systems is introduced to …
learning algorithm is presented. An adaptive kernel size using fuzzy systems is introduced to …
Minimum error entropy Kalman filter
To date, most linear and nonlinear Kalman filters (KFs) have been developed under the
Gaussian assumption and the well-known minimum mean square error (MMSE) criterion. In …
Gaussian assumption and the well-known minimum mean square error (MMSE) criterion. In …
Robust Kalman filters based on Gaussian scale mixture distributions with application to target tracking
In this paper, a new robust Kalman filtering framework for a linear system with non-Gaussian
heavy-tailed and/or skewed state and measurement noises is proposed through modeling …
heavy-tailed and/or skewed state and measurement noises is proposed through modeling …
Maximum correntropy unscented Kalman and information filters for non-Gaussian measurement noise
In this paper, we investigate the state estimation problem of nonlinear systems with non-
Gaussian measurement noise. Based on a newly defined cost function which is obtained by …
Gaussian measurement noise. Based on a newly defined cost function which is obtained by …
A new outlier-robust student's t based Gaussian approximate filter for cooperative localization
In this paper, a new outlier-robust Student's t based Gaussian approximate filter is proposed
to address the heavy-tailed process and measurement noises induced by the outlier …
to address the heavy-tailed process and measurement noises induced by the outlier …
A novel robust Kalman filter with unknown non-stationary heavy-tailed noise
In this article, the state estimation with unknown non-stationary heavy-tailed process and
measurement noises (HPMN) is considered. The measurement likelihood and the one-step …
measurement noises (HPMN) is considered. The measurement likelihood and the one-step …
Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication: Progress, Insights and Trends
W Song, Z Wang, Z Li, J Wang… - IEEE/CAA Journal of …, 2024 - ieeexplore.ieee.org
The nonlinear filtering problem has enduringly been an active research topic in both
academia and industry due to its ever-growing theoretical importance and practical …
academia and industry due to its ever-growing theoretical importance and practical …
Robust state of charge estimation for Li-ion batteries based on cubature kalman filter with generalized maximum correntropy criterion
Kalman filters (KFs) are widely used for state-of-charge (SOC) estimation of Li-ion batteries
due to their excellent dynamic tracking capability. Especially the cubature KF (CKF), with the …
due to their excellent dynamic tracking capability. Especially the cubature KF (CKF), with the …
An adaptive Kalman filter with inaccurate noise covariances in the presence of outliers
In this article, a novel variational Bayesian (VB) adaptive Kalman filter with inaccurate
nominal process and measurement noise covariances (PMNC) in the presence of outliers is …
nominal process and measurement noise covariances (PMNC) in the presence of outliers is …