• DocumentCode
    1001744
  • Title

    Centralised integration of multisensor noisy and fuzzy data

  • Author

    Hong, L. ; Wang, G.-J.

  • Author_Institution
    Dept. of Electr. Eng., Wright State Univ., Dayton, OH, USA
  • Volume
    142
  • Issue
    5
  • fYear
    1995
  • fDate
    9/1/1995 12:00:00 AM
  • Firstpage
    459
  • Lastpage
    465
  • Abstract
    The paper discusses centralised integration of multisensor noisy and fuzzy data, which employs both Kalman filtering and fuzzy arithmetic. Because of the property of fuzzy arithmetic, the parameter fuzziness in a system under extended operation will increase without limit and finally reach an unacceptable range. Hong and Wang adopted a new compression technique to solve this problem. This paper extends their work on single sensor noisy and fuzzy data filtering to multisensor noisy and fuzzy data filtering. An example is given to illustrate the effectiveness of the algorithm presented
  • Keywords
    Kalman filters; data compression; filtering theory; fuzzy set theory; sensor fusion; Kalman filtering; centralised integration; data compression; fuzzy arithmetic; fuzzy data; multisensor noisy data;
  • fLanguage
    English
  • Journal_Title
    Control Theory and Applications, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-2379
  • Type

    jour

  • DOI
    10.1049/ip-cta:19952020
  • Filename
    468420