Methods for Bayesian inference with nonlinear systems are of fundamental interest to a wide array of scientific and engineering disciplines, including signal processing, control systems, information fusion, robotics, and aerospace engineering. These techniques are essential for providing accurate state estimates of dynamic systems from noisy measurements in critical applications such as target tracking, autonomous navigation, sensor fusion, fault detection, and automated decision-making. While legacy Kalman filter-based methods provided a foundation for the field, their performance is often limited to systems with mild nonlinearities and perfect model knowledge. To address these limitations, this special session focuses on recent advances in advanced nonlinear state estimation, emphasizing the development of robust architectures, distributed fusion strategies for networked systems, and adaptive designs for complex discrete and continuous-time models. This topic is of paramount importance to both academia, as it pushes the boundaries of Bayesian and optimization-based inference, and industry, where there is an urgent demand for robust, scalable solutions that can operate in high-dimensional spaces and adversarial, real-world environments.

This special section focuses on advanced waveform design and its applications in radar signal processing areas, including but not limited to the following topics.

Related topics:

Nonlinear and Non-Gaussian Design: Sigma-point, particle flow, and stochastic integration-based design.

Robust and Constrained Estimation: Techniques for handling unexpected model behaviors and linearly/nonlinearly constrained states.

Distributed Fusion Architectures: Consensus-based cooperative estimation and fusion under communication-constrained or high-dynamic environments.

Intelligent Design: State estimator design aided by Machine Learning for parameter identification and model adaptation.

Joint and Dual Estimation: Simultaneous estimation for both system states and unknown model parameters.

Performance Analysis: Evaluation of existing nonlinear filtering methods and estimation consistency.

Practical Implementations and Case Studies: Application of advanced estimators in aerospace, robotics, and multi-sensor surveillance systems.

Important Dates:
Submission Deadline: May 25, 2026
Notification: June 15, 2026
Registration: June 30, 2026

Submit Method:
1, submit it via the link: http://www.easychair.org/conferences/?conf=icicsp2026 (after entering the link, click on the corresponding topic)
2, send your manuscript to icicsp@vip.163.com with subject "Submit+Special Session-17+Paper Title". (请通过邮件发送稿件，邮件题目：Submit+Special Session-17+Paper Title)

Short Biography of Organizers

1. Hongwei WANG, University of Electronic Science and Technology of China, China
Hongwei WANG is an Associate Professor at the University of Electronic Science and Technology of China (UESTC). He received his B.S. degree in 2013 and Ph.D. degree in 2019, both from Northwestern Polytechnical University (NPU), Xi'an, China. During his doctoral studies, he was a joint Ph.D. student at Nanyang Technological University, Singapore, and Stevens Institute of Technology, USA. From December 2019 to July 2024, he worked as a postdoctoral researcher at UESTC, and subsequently joined the faculty as an Associate Professor. In recent years, he has published more than 30 academic papers, led or participated in over 10 projects funded by the National Natural Science Foundation of China (NSFC) and other agencies, and serves as a member of the CIGRE D2 China Committee. His research interests include statistical signal processing, compressive sensing and sparse theory, robust state estimation, and system identification.

2. Jiacheng He, University of Electronic Science and Technology of China
Jiacheng HE is a postdoctoral researcher in Control Science and Engineering at the University of Electronic Science and Technology of China. He received his bachelor’s degree in Electrical Engineering and Automation from Henan University of Science and Technology, and his master’s and Ph.D. degrees in Mechanical Engineering from the University of Electronic Science and Technology of China. He also conducted joint training research at Nanyang Technological University. In recent years, he has published more than 30 academic papers in journals and conferences such as Automatica, Pattern Recognition, IEEE Transactions on Industrial Informatics, IEEE Transactions on Aerospace and Electronic Systems, and IEEE Transactions on Vehicular Technology. He has led projects including the China Postdoctoral Science Foundation and the Sichuan Provincial Natural Science Foundation. His research interests focus on robust modeling of unmanned systems, state estimation, non-Gaussian filtering and smoothing, distributed information fusion, target tracking, and trajectory reconstruction in the fields of intelligent perception and data computing.

3. Junyi Zuo, Northwestern Polytechnical University (NPU)
Junyi ZUO is an Associate Professor at Northwestern Polytechnical University (NPU), Xi'an, China. He received his B.S. degree in 2010 and Ph.D. degree in 2013, both from Northwestern Polytechnical University. In recent years, he has published more than 20 academic papers, authored/co-authored 2 books, and led or participated in multiple research projects funded by the National Natural Science Foundation of China (NSFC) and other agencies. His research interests include statistical signal processing, particle filtering, robust state estimation, and system identification.

4 Zihao Jiang, West Anhui University
Zihao Jiang received the Ph.D. degree from Harbin Engineering University in 2025. He is currently a lecturer with the School of Electrical and Photoelectronic Engineering, West Anhui University, also with the Research Institute of Embodied Intelligence and Brain-Computer Fusion, West Anhui University. His research interests include statistical signal processing and distributed state estimation. He has published more than ten papers in journals such as IEEE T-SP, IEEE T-CASII, IEEE CSL, IEEE IOT.

5 Ke Li, Jiangnan University
Li Ke received the Ph.D. degree from Jiangnan University in January 2025. She is currently an Associate Professor at Jiangnan University. Her research interests include intelligent state sensing, Bayesian estimation, and statistical signal processing. She has published more than ten papers in journals including IEEE/CAA Journal of Automatica Sinica, IEEE Transactions on Industrial Electronics, and IEEE Transactions on Industrial Informatics. She has filed five Chinese invention patent applications and is a member of IEEE, CAA, and JAA.

 

 

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