Belief exponential divergence for D-S evidence theory and its application in multi-source information fusion  

作　　者：DUAN Xiaobo FAN Qiucen BI Wenhao ZHANG An 

机构地区：[1]School of Aeronautics,Northwestern Polytechnical University,Xi’an 710072,China

出　　处：《Journal of Systems Engineering and Electronics》2024年第6期1454-1468,共15页系统工程与电子技术(英文版)

基　　金：supported by the National Natural Science Foundation of China(61903305,62073267);the Fundamental Research Funds for the Central Universities(HXGJXM202214).

摘　　要：Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.

关 键 词：Dempster-Shafer(D-S)evidence theory multi-source information fusion conflict measurement belief expo-nential divergence(BED) target recognition 

分 类 号：O17[理学—数学]