• DocumentCode
    2338363
  • Title

    Contribution of evidence-similarity to target classification

  • Author

    Li, Jian ; Lan, Jinhui

  • Author_Institution
    Dept. of Instrum. Sci. & Technol., Univ. of Sci. & Technol. Beijing, Beijing, China
  • fYear
    2012
  • fDate
    18-20 July 2012
  • Firstpage
    1822
  • Lastpage
    1826
  • Abstract
    To resolve the target classification problem under the condition of interference, the paper presents a target classification method based on the evidence-similarity. Because the results of Dempster-Shafer Theory (DST) and Dezert-Smarandache Theory (DSmT) are used in different conflict condition. In the low conflict situation, the classification by DST has good effect, but the classification by DSmT introduces the focal element, which increase the amount of computation greatly. In the high conflict situation, DSmT can effectively tackle the problem that the contradiction focal element can not be fused in DST, and avoid the DST classification appearing counterintuitive conclusions. Therefore, the two kinds of classification theories are combined by the similarity of evidence in the paper. Experiment results show that the method can effectively improve the accuracy of the target classification under different conflict condition.
  • Keywords
    inference mechanisms; pattern classification; sensor fusion; uncertainty handling; DST; DSmT; Dempster-Shafer theory; Dezert-Smarandache theory; evidence similarity; target classification; Magnetic sensors; Manganese; Reliability; Vectors; Vehicles; DST; PCR6; evidence-similarity; target classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2012 7th IEEE Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4577-2118-2
  • Type

    conf

  • DOI
    10.1109/ICIEA.2012.6361023
  • Filename
    6361023