Add to ORKGThe forward filtering solution to the Bayesian estimation problem provides the best possible solution for a probability density function given all past and current data. The backward smoothing solution, by contrast, makes use of all data over a fixed interval, through a fixed data lag, or beyond a fixed point in order to determine an improved solution for the probability density function. Achieving a better understanding of the probabilistic description of the state in orbit determination is key to providing reliable situational awareness. This paper investigates a method of combining forward filtering and backward smoothing solutions for non-Gaussian distributions in the orbit determination problem. A simulation of a low-Earth orbit tracki...
The Bingham-Gauss density quantifies the uncertainty of a state vector comprised of an attitude quat...
By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed ...
Abstract—In this paper, we address the problem of smoothing on Gaussian mixture (GM) posterior densi...
In many applications, there is an interest in systematically and sequentially estimating quantities ...
A method is developed to approximate the bearings-only orbit determination like-lihood function usin...
This paper investigates a smoothing method using the nonlinear Gaussian mixture probability hypothes...
International audienceSmoothers are increasingly used in geophysics. Several linear gaussian algorit...
We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochasti...
The use of Gaussian mixture model representations for nonlinear estimation is an attractive tool for...
Abstract—We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear ...
Consider analysis is an estimation technique that emerged in the 1960s to account for errors in syst...
Trajectory navigation entails the solution of many different problems that arise due to uncertain kn...
We formulate probabilistic numerical approximations to solutions of ordinary differential equations ...
We propose a closed-form Gaussian sum smoother and, more importantly, closed-form smoothing solution...
International audienceThis paper proposes a new Bayesian strategy for the estimation of smooth param...
The Bingham-Gauss density quantifies the uncertainty of a state vector comprised of an attitude quat...
By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed ...
Abstract—In this paper, we address the problem of smoothing on Gaussian mixture (GM) posterior densi...
In many applications, there is an interest in systematically and sequentially estimating quantities ...
A method is developed to approximate the bearings-only orbit determination like-lihood function usin...
This paper investigates a smoothing method using the nonlinear Gaussian mixture probability hypothes...
International audienceSmoothers are increasingly used in geophysics. Several linear gaussian algorit...
We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochasti...
The use of Gaussian mixture model representations for nonlinear estimation is an attractive tool for...
Abstract—We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear ...
Consider analysis is an estimation technique that emerged in the 1960s to account for errors in syst...
Trajectory navigation entails the solution of many different problems that arise due to uncertain kn...
We formulate probabilistic numerical approximations to solutions of ordinary differential equations ...
We propose a closed-form Gaussian sum smoother and, more importantly, closed-form smoothing solution...
International audienceThis paper proposes a new Bayesian strategy for the estimation of smooth param...
The Bingham-Gauss density quantifies the uncertainty of a state vector comprised of an attitude quat...
By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed ...
Abstract—In this paper, we address the problem of smoothing on Gaussian mixture (GM) posterior densi...