Other terms associated with data fusion that typically appear in the literature include decision fusion, data combination, data aggregation, multisensor data fusion, and sensor fusion.
In this sense, the term information fusion implies a higher semantic level than data fusion.
The terms information fusion and data fusion are typically employed as synonyms but in some scenarios, the term data fusion is used for raw data (obtained directly from the sensors) and the term information fusion is employed to define already processed data. In general, all tasks that demand any type of parameter estimation from multiple sources can benefit from the use of data/information fusion methods. These methods and algorithms are presented using three different categories: (i) data association, (ii) state estimation, and (iii) decision fusion. Then, the most common algorithms are reviewed. We first enumerate and explain different classification schemes for data fusion. This paper summarizes the state of the data fusion field and describes the most relevant studies. The integration of data and knowledge from several sources is known as data fusion.