ABSTRACT
This chapter discusses a recent data fusion algorithm, Fuzzy Information Fusion (FIF) that provides a general method, based on decision matrices, for fusing heterogeneous sources, into a single composite, with the final goal of rating and ranking alternatives. In addition, FIF has the ability to handle imprecise information, either from lack of confidence in the input data or from its imprecision. Data fusion is essentially a means of combining information from multiple sources into a single unified view of the various data. Data fusion includes three main types: multisensor, image, and information fusion. The waterfall model is a hierarchical architecture where the information output by one module will be input to the next module. This model focuses on the processing functions on the lower levels. The intelligence cycle is an approach that falls in a fusion model subgroup with cyclic character, with the Boyd control loop an integral part.
