首页    期刊浏览 2025年05月24日 星期六
登录注册

文章基本信息

  • 标题:Research on improved evidence theory based on multi-sensor information fusion
  • 本地全文:下载
  • 作者:Zhen Lin ; Jinye Xie
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2021
  • 卷号:11
  • 期号:1
  • 页码:1
  • DOI:10.1038/s41598-021-88814-3
  • 出版社:Springer Nature
  • 摘要:In view of the lack of effective information fusion model for heterogeneous multi-sensor, an improved Dempster/Shafer (DS) evidence theory algorithm is designed to fuse heterogeneous multi-sensor information. The algorithm first introduces the compatibility coefficient to characterize the compatibility between the evidence, obtains the weight matrix of each proposition, and then redistributes the basic probability distribution of each focal element to obtain a new evidence source. Then the concept of credibility is introduced, and the average support of evidence credibility and evidence focal element is used to improve the synthesis rule, so as to obtain the fusion result. Compared with other algorithms, the proposed algorithm can solve the problems existing in DS evidence theory when dealing with highly conflicting evidence to a certain extent, and the fusion results are more reasonable and the convergence speed is faster.
国家哲学社会科学文献中心版权所有