Multisensor data fusion is the process of combining observations from a number of different
sensors to provide a robust and complete description of an environment or process of …

This work presents the current state-of-the-art in techniques for tracking a number of objects
moving in a coordinated and interacting fashion. Groups are structured objects …

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 …

In this paper, an effective solution is proposed for joint beam and power scheduling (JBPS)
in the netted Colocated MIMO (C-MIMO) radar systems for distributed multi-target tracking …

A general framework for constructing and using probabilistic models of complex systems that
would enable a computer to use available information for making decisions. Most tasks …

Multitarget tracking (MTT) refers to the problem of jointly estimating the number of targets
and their states or trajectories from noisy sensor measurements. MTT has a long history …

Multisensor data fusion is an emerging technology applied to Department of Defense (DoD)
areas such as automated target recognition, battlefield surveillance, and guidance and …

Multiple hypothesis tracking (MHT) is generally accepted as the preferred method for solving
the data association problem in modern multiple target tracking (MTT) systems. This paper …

This is the fifth part of a series of papers that provide a comprehensive survey of techniques
for tracking maneuvering targets without addressing the so-called measurement-origin …

Decentralized Estimation and Control for Multisensor Systems explores the problem of
developing scalable, decentralized estimation and control algorithms for linear and …