A Method of Decision Fusion for Target Recognition Based on Grey Fixed Weight Clustering

The problem of decision fusion for target recognition is usually solved by the uncertainty information processing methods. This paper presents a novel algorithm of decision fusion for target recognition based on the grey fixed weight clustering analysis. The problem of recognizing M classes target is transformed into M problems of recognizing two classes target, and then each problem of recognizing two classes target is solved by the grey fixed weight clustering. The whitenization weight functions of each two classes are assessed by training samples. The experiment conducted on three classifiers and five classes radar target data demonstrates this method can effectively improve the recognition performance.