Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (6): 1454-1468.doi: 10.23919/JSEE.2024.000101

• SYSTEMS ENGINEERING • Previous Articles    

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

Xiaobo DUAN(), Qiucen FAN(), Wenhao BI(), An ZHANG()   

  • Received:2023-05-05 Online:2024-12-18 Published:2025-01-14
  • Contact: Wenhao BI E-mail:duanxiaobo@mail.nwpu.edu.cn;fanqc1006@mail.nwpu.edu.cn;biwenhao@nwpu.edu.cn;zhangan@nwpu.edu.cn
  • About author:
    DUAN Xiaobo was born in 1999. She received her B.S. degree in aircraft control and information engineering from Northwestern Polytechnical University, Xi’an, China, in 2022, where she is currently pursuing her M.S. degree in aerospace science and technology. Her research interests are information fusion and complex adaptive system. E-mail: duanxiaobo@mail.nwpu.edu.cn

    FAN Qiucen was born in 1996. He received his B.S. and M.S. degrees from School of Aeronautics at Northwestern Polytechnical University, Xi’an, China, in 2019 and 2022, respectively, where he is currently pursuing his Ph.D. degree in systems engineering. His research interests are design theory and model-based systems engineering. E-mail: fanqc1006@mail.nwpu.edu.cn

    BI Wenhao was born in 1986. He received his Ph.D. degree in system engineering from Northwestern Polytechnical University (NPU), Xi’an, China, in 2018. He is currently an associate researcher in NPU. His research interests are system engineering and control theory. E-mail: biwenhao@nwpu.edu.cn

    ZHANG An was born in 1962. He received his M.S. degree in systems engineering and Ph.D. degree in control theory and control engineering from Northwestern Polytechnical University (NPU), Xi’an, China, in 1986 and 1999, respectively. He is currently a professor in NPU. His research interests are complex system modeling, decision theory, and simulation and performance evaluation. E-mail: zhangan@nwpu.edu.cn
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61903305;62073267), and the Fundamental Research Funds for the Central Universities (HXGJXM202214).

Abstract:

Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion. Nevertheless, when fusing highly conflicting evidence it may produce counterintuitive outcomes. To address this issue, a fusion approach based on a newly defined belief exponential divergence 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 examples. Additionally, the proposed approach is applied to aerial target 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.

Key words: Dempster-Shafer (D-S) evidence theory, multi-source information fusion, conflict measurement, belief exponential divergence (BED), target recognition