In the last two decades, research on multi-sensor information fusion has burgeoned with the prosperity of wireless sensor networks and multi-sensor systems, where the information from different sensors, as well as various apriori knowledges, is integrated to support better decision. A multi-sensor networked system is composed of a number of cost-effective sensors (a.k.a. agents) with limited sensing, computing and communication capabilities which, however, enjoys the advantages in terms of low power consumption and simple installation with high performance and strong reliability. In the core of most multi-sensor/networked systems are the multi-sensor information fusion technology for various purposes such as sensor registration and control, network consensus and collaboration, network topological design/analysis, resource allocation and management, and so on. In addition, understanding how the system performs and evolves from the information-theoretic perspective is also important and derives relevant theoretical studies. This is often critical in the regard of many important problems such as managing a limited number of sensors for the best field-of-view coverage in motion monitoring, tackling the intrinsic interactions/failures of local sensors, trade-off between performance and computing/communication resources, to name just a few. These problems are imperative but also challenging for which various theories, techniques and algorithms are continuously being proposed and developed, but it is still calling for more research efforts and endeavors.
This Special Issue of Journal of Beijing Institute of Technology aims at collecting high-quality papers within the general research field of multi-sensor information fusion. All original research papers, as well as survey/review/tutorial papers, on the following and relevant topics are welcome.
Topics of interest include (but are not limited to):
● Multi-sensor Kalman filtering, multi-sensor particle filtering, multi-sensor multi-scale filtering
●Multi-sensor random finite set (RFS) approaches, e.g., Arithmetic average RFS filtering
●Multi-sensor (multiple) target detection, tracking, recognition and classification
●Networked radar, radar network, radar signal fusion and enhancement
●Wireless netted sensor registration, synchronization, control, and management
●Resource-aware management for multi-sensor systems
●Average consensus based on wireless sensor network
●Massage passing, belief propagation, factor graphs
●Multi-agent system-based filtering and control
●Distributed and networked control systems
●Networked autonomous vehicles, Formation/containment control
●Multi-sensor possibility theory and reasoning methods
●Bayesian networks, multi-sensor neural network
●Multi-sensor data clustering, learning and inference
●Secure fusion estimation and decision
All submissions will be peer reviewed according to the Journal of Beijing Institute of Technology guidelines. The contributions should be original and have not been published or submitted elsewhere.
Manuscript should be submitted online viahttps://mc03.manuscriptcentral.com/jbitin the classification “202206-Multi-sensor Information Fusion”. Prospective authors may consult the site http://journal.bit.edu.cn/jbit for more information for submission.
Schedule:
Submission deadline: July 15, 2022;
Publication date: December 25, 2022
Guest Editors:
Tiancheng Li,Professor, Northwestern Polytechnical University, Xi’an, China
Email: t.c.li@nwpu.edu.cn
Bo Chen,Professor, Zhejiang University of Technology, Hangzhou, China,
Email: bchen@zjut.edu.cn
Shenghua Zhou,Professor, Xidian University, Xi’an, China
Email: shzhou@mail.xidian.edu.cn
Enbin Song,Professor, Sichuan University, Chengdu, China
Email: ebsong@scu.edu.cn
Xingshuai Qiao,Postdoc, Tsinghua University, Beijing, China
Email: Qiaoxs@mail.tsinghua.edu.cn
