Information Fusion over Network Dynamics with Unknown Correlations: An Overview

信息融合 人气 计算机科学 领域(数学) 传感器融合 融合 数据科学 人工智能 心理学 数学 社会心理学 语言学 哲学 纯数学
作者
Wangyan Li,Fang Yang
标识
DOI:10.53941/ijndi0201003
摘要

Survey/review study Information Fusion over Network Dynamics with Unknown Correlations: An Overview Wangyan Li 1, and Fuwen Yang 2,* 1 College of Science, University of Shanghai for Science and Technology, Shanghai 200093, China 2 Griffth School of Engineering, Griffth University, Gold Coast Campus, QLD 4222, Australia * Correspondence: fuwen.yang@griffth.edu.au Received: 24 October 2022 Accepted: 22 November 2022 Published: Abstract: Unknown correlations (UCs) generally exist in a wide spectrum of practical multi-source information fusion problems, and thereby, their corresponding fusion problems have become one of the most important topics in information fusion domain. During the past three decades, the research on this topic has been growing rapidly and extensively, and, as a result, various important advances have been reported. In this overview, we intend to summarize the culmination of years of development in the field of information fusion under UCs as a roadmap. First, the potential reasons leading to UCs are investigated. According to the unknown nature of correlations, we further divide UCs into two categories, i.e., fully UCs, and partially UCs. For each category, the corresponding fusion methods are reviewed. Next, this roadmap witnesses the recent development of information fusion under UCs in a distributed way thanks to the popularity of distributed sensing technology. In particular, the distributed fusion techniques based on consensus, diffusion, and multi-object tracking strategies for UCs are examined. Finally, some future perspectives on information fusion under UCs are pointed out.
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