A method of Distributed Decision Fusion based on SVM and D-S evidence theory

Dempster-Shafer (D-S) evidence theory is an effective method used for Distributed Decision Fusion (DDF). However, constructing a basic probability assignment function (BPAF) is a challenging task for practical fusion applications. This paper proposes a novel method for DDF of target identification. In the presented algorithm, Support Vector Machine (SVM) is utilized as the identifier, and the basic probability assignment function is constructed accordingly. The final fused results are obtained by applying the D-S evidence theory to the outputs of the identifiers. The experimental results show that the proposed method provides higher accuracy and reliability when it is compared with existing voting schemes.