‌Dear Colleagues,

Multi-sensor multitarget tracking involves integrating data from diverse sensors to enhance the tracking performance, aiming to ascertain target positions. Despite considerable progress in fusion strategies and tracking methodologies, numerous challenges persist, propelled by technological advancements. For example, the tracking process often encounters problems such as uncertain motion models, difficult target initiation and uncertain data association. In addition, factors such as different sensor fields of view, spatiotemporal misalignment, and heterogeneous filter fusion emphasize the necessity of designing robust fusion criteria to ensure tracking robustness. We advocate the introduction of new algorithms and explore practical solutions, including centralized/distributed fusion tracking techniques in tracking scenarios with different target types.

The Special Issue covers multiple target types, including point target, extended target and group target. For this reason, we have conceived this Special Issue, whose purpose is to gather the many researchers operating in the field to contribute to a collective effort in understanding the trends and future questions in the field of multi-sensor multitarget tracking. Topics include, but are not limited to:

• Centralized/distributed fusion frameworks

• Multitarget tracking based on random finite set theory

• Multitarget tracking based on message passing

• Multi-sensor extended target tracking

• Multi-sensor group target tracking

• Multi-sensor fusion tracking based on deep learning

• Heterogeneous filtering fusion

• Multi-sensor possibility theory and reasoning methods

• Integrated detection and tracking

• Resource management/allocation

• Threat assessment and sensor control for multitarget tracking