In this study, we provide an overview of recent advances in multisensor multitarget tracking
based on the random finite set (RFS) approach. The fusion that plays a fundamental role in …

This tutorial introduces state-of-the-art methods for tracking multiple spatially extended
objects based on unlabeled noisy point clouds, eg, from radar or lidar sensors. In the first …

This article provides an elaborate overview of current research in extended object tracking.
We provide a clear definition of the extended object tracking problem and discuss its …

This paper presents a Gaussian-mixture (GM) implementation of the probability hypothesis
density (PHD) filter for tracking extended targets. The exact filter requires processing of all …

<? Pub Dtl=""?> This paper presents a cardinalized probability hypothesis density (CPHD)
filter for extended targets that can result in multiple measurements at each scan. The …

The random hypersurface model (RHM) is introduced for estimating a shape approximation
of an extended object in addition to its kinematic state. An RHM represents the spatial extent …

Extended object tracking considers the simultaneous estimation of the kinematic state and
the shape parameters of a moving object based on a varying number of noisy detections …

Multiple radar systems represent an attractive option for target tracking because they can
significantly enlarge the area coverage and improve both the probability of trajectory …

In this work, we present a novel method for tracking an elliptical shape approximation of an
extended object based on a varying number of spatially distributed measurements. For this …

This correspondence proposes a new measurement update for extended target tracking
under measurement noise when the target extent is modeled by random matrices …