Special Session 21  会议特别专题 21

Multi-Source Perception and Tracking Fusion for Intelligent Sensing Systems

Description: Multi-source perception and tracking fusion has become a core enabling technology for intelligent sensing systems in autonomous driving, robotics, unmanned platforms, and industrial automation. By combining information from heterogeneous sensing modalities, such as radar, LiDAR, infrared sensors, and communication-assisted sensing, perception systems can achieve improved robustness, accuracy, and situational awareness in complex and dynamic environments. Despite its great potential, significant challenges remain in practical deployment. These include sensor heterogeneity, spatial-temporal synchronization, calibration errors, uncertainty propagation, clutter and occlusion, and incomplete observations. In addition, robust target tracking and fusion in dense, adversarial, or degraded environments require new approaches that jointly exploit complementary sensing information and advanced learning-based or model-based methods.
This special session aims to bring together researchers and practitioners from academia and industry to present the latest advances in multi-source perception, target tracking, and fusion methodologies. The session will provide a focused platform for discussing theories, algorithms, architectures, datasets, benchmarks, and real-world applications for next-generation intelligent sensing and tracking systems.

Session organizers
Assoc. Prof. Guchong Li, Northwestern Polytechnical University, China
Dr. Yaowen Li, Tsinghua University, China
Assoc. Prof. Tuanwei Tian, Henan University, China

The topics of interest include, but are not limited to:
▪ Heterogeneous sensor data fusion for intelligent sensing
▪ Multi-sensor target detection, recognition, and localization
▪ Single-target and multi-target tracking
▪ Integrated sensing and communication (ISAC) system design
▪ Distributed and cooperative tracking fusion
▪ Multi-modal data fusion
▪ Integrated Radar and Communication System
▪ Deep learning and transformer-based methods for perception and tracking fusion
▪ Sensor registration, calibration, and synchronization
▪ Real-time embedded implementation for fusion and tracking systems

Submission method
Submit your Full Paper (no less than 5 pages with two colums) or your paper abstract-without publication (200-400 words) via Online Submission System, then choose Special Session 21 (Multi-Source Perception and Tracking Fusion for Intelligent Sensing Systems)
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Introduction of Session organizer

Assoc. Prof. Guchong Li, Northwestern Polytechnical University, China

Guchong Li received the B.S. degree in electrical engineering and the Ph.D. degree in information and communication engineering from the University of Electronic Science and Technology of China, Chengdu, China, in 2016 and 2021, respectively. From 2018 to 2020, he was a Visiting Student with the Dipartimento di Ingegneria dell’Informazione, Università di Firenze, Firenze, Italy. From 2021 to 2023, he was a Postdoctoral Fellow with the Department of Electronic Engineering, Tsinghua University, Beijing, China. He is currently an Associate Professor with the Northwestern Polytechnical University, Xi’an, China. His research interests include random finite set, target tracking, and multisensor data fusion.



Dr. Yaowen Li, Tsinghua University, China

Yaowen Li, Tsinghua University. He received the B.S. and Ph.D. degrees in electronic engineering from Tsinghua University, Beijing, China, in 2017 and 2022, respectively. He is currently an Assistant Researcher with Tsinghua University. His main research interests include radar data processing, multitarget tracking, and multisensor information fusion.



Assoc. Prof. Tuanwei Tian, Henan University, China

Tuanwei Tian was born in 1988, received the Ph.D. degree in 2021. He is currently an Associate Professor with the School of Physics and Electronic Engineering, Henan University, Kaifeng, China. His research interests include the communication and radar signal processing and reconfigurable intelligent surface, particularly with the radar-communication integration.