• DocumentCode
    2497472
  • Title

    An improved robust fusion method based on density estimation

  • Author

    Guo, Yunfei ; Xue, Anke ; Lin, Yuesong ; Peng, DongLiang

  • Author_Institution
    Inst. of Inf. & Control Technol., Hangzhou Dianzi Univ., Hangzhou
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    7576
  • Lastpage
    7581
  • Abstract
    To solve the uncertain information fusion problem, we define the robust performance of the fusion algorithm and propose an improved density estimation based robust fusion algorithm. First, the mean-shift procedure is employed in detecting the dominant mode of the information density function; second, the max iterative time is calculated according to the real time request; last, all the valid data in the dominant field after the max iterative time are fused. The presented algorithm is compared with the weighted fusion method and the density estimation fusion technique in two simulation cases. The results show that it is more accurate and robust and satisfies the system real time request.
  • Keywords
    information theory; sensor fusion; density estimation fusion; information density function; max iterative time; mean-shift procedure; robust fusion algorithm; uncertain information fusion prolem; weighted fusion method; Automation; Density functional theory; Intelligent control; Iterative algorithms; Kernel; Real time systems; Robust control; Robustness; density estimation; robust fusion; uncertain information;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4594105
  • Filename
    4594105