• DocumentCode
    1845734
  • Title

    Multi-scale fusion and estimation for multi-resolution sensors

  • Author

    Yuemin Li ; Renbiao Wu ; Tao Zhang

  • Author_Institution
    Tianjin Key Lab. for Adv. Signal Process., Civil Aviation Univ. of China, Tianjin, China
  • Volume
    1
  • fYear
    2012
  • fDate
    21-25 Oct. 2012
  • Firstpage
    193
  • Lastpage
    197
  • Abstract
    On the basis of theory for Discrete Wavelet Transform (DWT) of signal statistical characteristics and Dynamic Multi-scale System (DMS) of the state transition model, a novel algorithm for multi-scale fusion and estimation with multi-resolution sensors is derived. In order to construct a uniform resolution model of Kalman Filter, the equations of state and measurement are processed with DWT at different resolution levels, and then the measurements of the same resolution level are fused and filtered. Experimental results indicate that the proposed method is more effective than other existing algorithms.
  • Keywords
    discrete wavelet transforms; estimation theory; sensor fusion; signal processing; DMS; DWT; Kalman Filter; discrete wavelet transform; dynamic multiscale system; multiresolution sensors; multiscale estimation; multiscale fusion; signal statistical characteristics; state transition model; Kalman filter; discrete wavelet transform; dynamic multi-scale system; fusion and estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2012 IEEE 11th International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2164-5221
  • Print_ISBN
    978-1-4673-2196-9
  • Type

    conf

  • DOI
    10.1109/ICoSP.2012.6491633
  • Filename
    6491633