A Multisource Situation Information Fusion Method Based on Dynamic Evidence Combination

Abstract

To address the problems of fusion efficiency, detection rate (DR), and false detection rate (FDR) that are associated with existing information fusion methods, a multisource information fusion method featuring dynamic evidence combination based on layer clustering and improved evidence theory is proposed in this study. First, the original alerts are hierarchically clustered and conflicting evidence is eliminated. Then, dynamic evidence combination is applied to fuse the condensed alerts, thereby improving the efficiency and accuracy of the fusion. The experimental results show that the proposed method is superior to current fusion methods in terms of fusion efficiency, DR, and FDR.