Herein is presented an efficient nonlinear filtering algorithm called the Gaussian-sum cubature Kalman filter (GSCKF) for the bearings-only tracking problem. It is developed based on the recently proposed cubature Kalman filter and is built within a Gaus
In a recent paper [1], we derived a new discrete-time Bayesian filter, which we have named the cubat...
Standard Bayesian filtering algorithms only work well when the statistical properties of system nois...
Bearings-only tracking only adopts measurements from angle sensors to realize target tracking, thus,...
This letter presents a Gaussian-sum cubature Kalman filter with improved robustness compared to the ...
In this paper, a fixed-lag and a fixed-interval Gaussian-sum cubature Kalman smoother are proposed f...
Passive tracking techniques for non-cooperative space target have great significance in space survei...
The paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic systems for...
AbstractThe paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic sys...
Abstract—To resolve the tracking problem of nonlinear/non-Gaussian systems effectively, this paper p...
a b s t r a c t The cubature Kalman filter (CKF) is a relatively new addition to derivative-free app...
One the most important problems in target tracking are state estimation. This paper deals on estimat...
A novel fifth-degree strong tracking cubature Kalman filter is put forward to improve the two-dimens...
A novel spherical simplex Gauss–Laguerre quadrature cubature Kalman filter is proposed to improve th...
Abstract—In this paper, we present a new nonlinear filter for high-dimensional state estimation, whi...
A nonlinear filter called the iterated modified gain extended Kalman filter (IMGEKF) is presented in...
In a recent paper [1], we derived a new discrete-time Bayesian filter, which we have named the cubat...
Standard Bayesian filtering algorithms only work well when the statistical properties of system nois...
Bearings-only tracking only adopts measurements from angle sensors to realize target tracking, thus,...
This letter presents a Gaussian-sum cubature Kalman filter with improved robustness compared to the ...
In this paper, a fixed-lag and a fixed-interval Gaussian-sum cubature Kalman smoother are proposed f...
Passive tracking techniques for non-cooperative space target have great significance in space survei...
The paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic systems for...
AbstractThe paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic sys...
Abstract—To resolve the tracking problem of nonlinear/non-Gaussian systems effectively, this paper p...
a b s t r a c t The cubature Kalman filter (CKF) is a relatively new addition to derivative-free app...
One the most important problems in target tracking are state estimation. This paper deals on estimat...
A novel fifth-degree strong tracking cubature Kalman filter is put forward to improve the two-dimens...
A novel spherical simplex Gauss–Laguerre quadrature cubature Kalman filter is proposed to improve th...
Abstract—In this paper, we present a new nonlinear filter for high-dimensional state estimation, whi...
A nonlinear filter called the iterated modified gain extended Kalman filter (IMGEKF) is presented in...
In a recent paper [1], we derived a new discrete-time Bayesian filter, which we have named the cubat...
Standard Bayesian filtering algorithms only work well when the statistical properties of system nois...
Bearings-only tracking only adopts measurements from angle sensors to realize target tracking, thus,...