Hybrid fuzzy - Genetic technique for multisensor fusion

This paper describes a novel hierarchical fuzzy-genetic information fusion technique. The reasoning takes place by means of fuzzy aggregation functions, capable of combining information by compensatory connectives that better mimic the human reasoning process than union and intersection, employed in traditional set theories. The parameters of the connectives are found by genetic algorithms. The distinctive feature of the algorithm developed is its capability of fusing data in a near optimal manner when no information about the reliability of the information sources, the degree of redundancy/complementarity of the information sources, and the structure of the hierarchy exists.