多源信息融合研究进展综述

A review of research advances in multi-source information fusion

多源信息融合是指将来自多个不同来源的数据和信息整合、分析和处理,以提高决策的准确性和效率。随着信息技术和数据采集技术的飞速发展,不同机构和组织获取和管理大量的数据和信息,这些数据和信息往往具有不同的格式、结构、精度和可靠性。因此,如何有效地整合和利用这些数据和信息成为了一个重要的问题。为此,对多源信息融合的功能模型、层次结构和系统结构进行研究,并重点梳理了多源信息融合中的方法,包括估计理论方法、不确定性推理方法和人工智能方法。详细介绍了这些方法的特点和应用现状,以帮助读者深入了解和掌握这些方法。最后,通过总结多源信息融合未来可能的发展趋势,为相关领域的研究和应用提供参考依据。

Multi-source information fusion refers to the integration,analysis and processing of data and information from several different sources to improve the accuracy and efficiency of decision making.With the rapid development of information technology and data collection techniques,different agencies and organizations acquire and manage a large amount of data and informa-tion,which often have different formats,structures,accuracy and reliability.Therefore,how to effectively integrate and utilize these data and information has become an important issue.To this end,extensive research has been conducted on the functional models,hierarchical structures,and system architectures for multi-source information fusion.The focus has been on outlining various methods employed in multi-source information fusion,including estimation theory,uncertainty reasoning,and artificial intelligence methods.These methods’characteristics and current applications are thoroughly discussed to provide readers with an in-depth understanding and proficiency in utilizing these approaches.Finally,potential future trends in multi-source information fusion are summarized,offering a reference basis for research and applications in relevant fields.