The cubature Kalman filter (CKF) has poor performance in strongly nonlinear systems while
the cubature particle filter has high computational complexity induced by stochastic …

Many filters have been proposed in recent decades for the nonlinear state estimation
problem. The linearization-based extended Kalman filter (EKF) is widely applied to …

The cubature Kalman filter (CKF) is more preferred over the unscented Kalman filter (UKF)
for its more stable performance. The CKF employs a third-degree spherical-radial cubature …

In this study, a novel robust measure of non‐linearity‐based cubature Kalman filter
(RMoNCKF) is proposed to obtain good performance with lower computational burden. The …

In this paper, a new variational Bayesian adaptive cubature Kalman filter (VBACKF) is
proposed for nonlinear state estimation. Although the conventional VBACKF performs better …

Square-root cubature Kalman filter (SCKF) is more effective for nonlinear state estimation
than an unscented Kalman filter. In this paper, we study the design of nonlinear filters based …

For a state estimation problem of nonlinear system, the square-root cubature Kalman filter
(SCKF) is an effective method when the noise statistical characteristics are known. However …

This study analyses the estimation error behaviour of the discrete-time cubature Kalman
filter (CKF) for general nonlinear systems with nonlinear measurements. First, we show that …

The maximum correntropy unscented Kalman filter (MCUKF) is a newly proposed non-linear
state estimation algorithm that is robust to non-Gaussian noise. In this paper, we propose …

During the recursive calculate process of the cubature Kalman filter (CKF), the covariance
matrix tends to lose positive definiteness and noise statistical characteristics are inaccurate …