A data-driven modeling approach to multi-source information fusion system

This paper addresses the problem of the uncertainty description for multi-source information fusion. Based on the uncertainty description, an overall framework of data-driven multi-source information fusion is discussed. In this framework, the theoretical models existed in traditional algorithms are reasonably reserved or modified, experimental evidence and background theory are collaboratively worked in fusion process. Through the core data-driven engine, a loop between the traditional fusion process and performance evaluation is established, where the feedback information from evaluation can be used to adjust the fusion process.