In this paper, a fixed-lag and a fixed-interval Gaussian-sum cubature Kalman smoother are proposed for the bearings-only tracking problem. The smoothers are of the forward-backward type and they utilise the Gaussian-sum cubature Kalman filter with improved robustness presented by the authors in [1]. Simulation results show that both the fixed-lag and fixed-interval smoothers exhibit improved accuracy over their filtering counterpart and outperform other existing smoothers of the same type for this problem, with the root-mean-square error overlapping the Cramér-Rao lower bound
A novel fifth-degree strong tracking cubature Kalman filter is put forward to improve the two-dimens...
Novel auxiliary truncated unscented Kalman filtering (ATUKF) is proposed for bearings-only maneuveri...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...
This letter presents a Gaussian-sum cubature Kalman filter with improved robustness compared to the ...
Herein is presented an efficient nonlinear filtering algorithm called the Gaussian-sum cubature Kalm...
a b s t r a c t The cubature Kalman filter (CKF) is a relatively new addition to derivative-free app...
Bearings-only tracking only adopts measurements from angle sensors to realize target tracking, thus,...
Although simple to implement, a bearing-only tracker using an extended Kalman filter mounted on a st...
In this paper, we study a nonlinear bearing-only target tracking problem using four different estima...
In bearings-only target tracking, the pseudo-linear Kalman filter (PLKF) attracts much attention bec...
In this paper, an improved nonlinear Gaussian mixture probability hypothesis density (GM-PHD) filter...
The Bearings-only tracking problem is to estimate the state of a moving object from noisy observati...
One the most important problems in target tracking are state estimation. This paper deals on estimat...
This paper presents a new approach for single sensor tracking using passive bearings only measuremen...
A primary cause of degraded performance in pointing and tracking systems is the jitter in the line o...
A novel fifth-degree strong tracking cubature Kalman filter is put forward to improve the two-dimens...
Novel auxiliary truncated unscented Kalman filtering (ATUKF) is proposed for bearings-only maneuveri...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...
This letter presents a Gaussian-sum cubature Kalman filter with improved robustness compared to the ...
Herein is presented an efficient nonlinear filtering algorithm called the Gaussian-sum cubature Kalm...
a b s t r a c t The cubature Kalman filter (CKF) is a relatively new addition to derivative-free app...
Bearings-only tracking only adopts measurements from angle sensors to realize target tracking, thus,...
Although simple to implement, a bearing-only tracker using an extended Kalman filter mounted on a st...
In this paper, we study a nonlinear bearing-only target tracking problem using four different estima...
In bearings-only target tracking, the pseudo-linear Kalman filter (PLKF) attracts much attention bec...
In this paper, an improved nonlinear Gaussian mixture probability hypothesis density (GM-PHD) filter...
The Bearings-only tracking problem is to estimate the state of a moving object from noisy observati...
One the most important problems in target tracking are state estimation. This paper deals on estimat...
This paper presents a new approach for single sensor tracking using passive bearings only measuremen...
A primary cause of degraded performance in pointing and tracking systems is the jitter in the line o...
A novel fifth-degree strong tracking cubature Kalman filter is put forward to improve the two-dimens...
Novel auxiliary truncated unscented Kalman filtering (ATUKF) is proposed for bearings-only maneuveri...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...