Algorithm for Target Recognition Based on Interval-Valued Intuitionistic Fuzzy Sets with Grey Correlation

Abstract

In order to improve exact recognition ratios for aerial targets, this paper presents a novel algorithm for target recognition based on interval-valued intuitionistic fuzzy sets with grey correlation. Drawbacks of some previously proposed methods are analyzed, and then a novel algorithm is presented. Recognition matrix of an aerial target is established first. Every entry associated with the matrix is an interval-valued intuitionistic fuzzy number, which is composed of interval-valued membership and nonmembership, representing the relation of the target to one category in terms of one characteristic parameter. Then grey correlation theory is used to analyze the recognition matrix to obtain the grey correlation degree of this unknown target to every category. 200 sets of target recognition data are used to compare the proposed algorithm with traditional methods. Experimental results verify that the correct recognition ratio can be up to 99.5% that satisfies the expectations, which shows the proposed algorithm can solve the target recognition problems better. The proposed algorithm can be used to solve the uncertain inference problems, such as target recognition, threat assessment, and decision making.