Advances in Multitarget Tracking and Applications

Dear Colleagues,

Tracking multiple targets remains a classic yet enduring topic of research in both civil and defense applications. Active areas of investigation include data association for point or extended targets with measurements, tracking in multipath environments, multitarget tracking using specialized sensors such as superpositional and imaging sensors, and robust algorithms that handle unknown detection probabilities, clutter, or noise profiles, among others. Recent advancements in multisensor systems have facilitated surveillance over vast areas, but they also introduce new challenges. Multisensor multitarget tracking can operate in centralized or distributed modes, with centralized approaches typically offering superior performance at the expense of limited scalability. In distributed algorithms, sensor nodes can flexibly exchange measurements, intermediate products, local posteriors, or combinations thereof. Much of the existing literature focuses on exchanging and fusing local posteriors, with numerous fusion criteria proposed to optimize this process.

Regarding specific methodologies, traditional tracking algorithms encompass batch processing via maximum-likelihood estimation, multiple hypothesis tracking, joint probabilistic data association, and related techniques. Over the past two decades, researchers have increasingly focused on algorithms that integrate random finite set theory with Bayesian frameworks. These methods simultaneously address target birth and death alongside tracking, while incorporating models for missed detections and clutter into the Bayesian iterations, resulting in more mathematically elegant solutions. Scalable fusion algorithms grounded in random finite set theory have also emerged in recent years to support distributed multitarget tracking in networked radar systems. More recently, message passing or belief propagation algorithms have gained prominence as efficient and accurate approaches for multisensor multitarget tracking.

In this Special Issue, we aim to collect contributions reporting recent developments in multisensor and multitarget tracking. The scope of this Special Issue includes (but is not limited to) the following:

• Multitarget tracking algorithms;
• Multidetection multitarget tracking;
• Multitarget tracking based on special sensors;
• Scalable multisensory multitarget tracking algorithms;
• Distributed fusion algorithms;
• Extended-target tracking algorithms;
• Robust multitarget tracking algorithms;
• Variational Bayes approaches for multisensor multitarget tracking;
• Joint tracking and sensor registration;
• Source management for multisensory and multitarget tracking applications;
• Artificial intelligence approaches for multisensory multitarget tracking.

Dr. Lin Gao
Dr. Chaoqun Yang
Guest Editors

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• multitarget tracking
• distributed fusion
• random finite set
• information fusion
• extended targets
• variational Bayes algorithms