This paper presents an overview of the extended target tracking research undertaken at the division of Automatic Control at Linköping University. The PHD and CPHD filters for multiple extended target tracking under clutter and unknown association are summarized, with focus on the Gaussian mixture and Gaussian inverse Wishart implementations. The paper elaborates on measurement set partitioning, the measurement generating Poisson rates, the probability of detection, and practical examples of measurement models.CADICSExtended Target TrackingCUA
This paper presents the integration of a spline based extension model into a probability hypothesis ...
Use of the Gaussian inverse Wishart probability hypothesis density (GIW-PHD) filter has demonstrated...
This paper presents a gamma-Gaussian-inverse Wishart (GGIW) implementation of a Poisson multi-Bernou...
Abstract—This paper presents an overview of the extended target tracking research undertaken at the ...
This paper presents a Gaussian-mixture implementation of the phd filter for tracking extended target...
In extended target tracking, targets potentially produce more than one measurement per time step. Mu...
In extended target tracking, targets potentially produce more than one measurement per time step. Mu...
This paper presents a Gaussian-mixture (GM) implementation of the probability hypothesis density (PH...
Abstract—This paper presents a Gaussian-mixture implemen-tation of the PHD filter for tracking exten...
This paper presents a random set based approach to tracking of an unknown number of extended targets...
This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets...
This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets...
This paper addresses extended multi-target tracking in clutter, i.e. tracking targets that may produ...
Abstract—This paper presents a cardinalized probability hy-pothesis density (CPHD) filter for extend...
This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets...
This paper presents the integration of a spline based extension model into a probability hypothesis ...
Use of the Gaussian inverse Wishart probability hypothesis density (GIW-PHD) filter has demonstrated...
This paper presents a gamma-Gaussian-inverse Wishart (GGIW) implementation of a Poisson multi-Bernou...
Abstract—This paper presents an overview of the extended target tracking research undertaken at the ...
This paper presents a Gaussian-mixture implementation of the phd filter for tracking extended target...
In extended target tracking, targets potentially produce more than one measurement per time step. Mu...
In extended target tracking, targets potentially produce more than one measurement per time step. Mu...
This paper presents a Gaussian-mixture (GM) implementation of the probability hypothesis density (PH...
Abstract—This paper presents a Gaussian-mixture implemen-tation of the PHD filter for tracking exten...
This paper presents a random set based approach to tracking of an unknown number of extended targets...
This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets...
This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets...
This paper addresses extended multi-target tracking in clutter, i.e. tracking targets that may produ...
Abstract—This paper presents a cardinalized probability hy-pothesis density (CPHD) filter for extend...
This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets...
This paper presents the integration of a spline based extension model into a probability hypothesis ...
Use of the Gaussian inverse Wishart probability hypothesis density (GIW-PHD) filter has demonstrated...
This paper presents a gamma-Gaussian-inverse Wishart (GGIW) implementation of a Poisson multi-Bernou...