Autonomous vehicles (AVs) rely on advanced sensory systems, such as Light Detection and
Ranging (LiDAR), to function seamlessly in intricate and dynamic environments. LiDAR …

This paper presents two trajectory Poisson multi-Bernoulli (TPMB) filters for multi-target
tracking: one to estimate the set of alive trajectories at each time step and another to …

Compared to the probability hypothesis density (PHD) and cardinalized PHD (CPHD) filters,
the trajectory PHD (TPHD) and trajectory CPHD (TCPHD) filters are for sets of trajectories …

In this article, we present the TMM-TPHD and TMM-TCPHD filters, which are the alternative
trajectory probability hypothesis density (TPHD) and the alternative trajectory cardinality …

This paper presents a general solution for computing the multi-object posterior for sets of
trajectories from a sequence of multi-object (unlabelled) filtering densities and a multi-object …

Multi-object tracking (MOT) refers to the process of estimating object trajectories of interest
based on sequences of noisy sensor measurements obtained from multiple sources …

This study proposes a novel solution using sensors with limited sensing range to estimate
the random appearance or disappearance of multi-object trajectories with unknown object …

This paper presents two new trajectory probability hypothesis density (TPHD) and trajectory
cardinality probability hypothesis density (TCPHD) filters for joint tracking and classification …

With the great development of Multi-Target Tracking (MTT) technologies, many MTT
algorithms have been proposed with their own advantages and disadvantages. Due to the …

To account for joint tracking and classification (JTC) of multiple targets from observation sets
in presence of detection uncertainty, noise and clutter, this paper develops a new trajectory …