• DocumentCode
    696652
  • Title

    Modeling radar data with time series models

  • Author

    de Waele, S. ; Broersen, P.M.T.

  • Author_Institution
    Dept. of Applied Physics, Delft University of Technology, P. O. Box 5046, 2600 GA Delft, The Netherlands
  • fYear
    2000
  • fDate
    4-8 Sept. 2000
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In Frequency Modulated Continuous Wave (FMCW) radar, the Fast Fourier Transform (FFT) is very efficient in separating reflections from various range cells. For the subsequent determination of the Doppler spectrum, the FFT is less suitable. The raw FFT is very erratic, while the smoothed FFT is limited in the spectral shapes it can accurately describe. For determination of the Doppler spectrum, ARMAsel time series analysis is better than the FFT. With ARMAsel time series analysis, an ARMA model is estimated from the data. The Doppler spectrum can be calculated from the ARMA-parameters. The model order and type are determined automatically from the data. Improved accuracy in comparison to other time series techniques is obtained by using robust estimation algorithms and order selection criteria, and by selecting automatically between several model types.
  • Keywords
    Biological system modeling; Data models; Doppler effect; Estimation; Mathematical model; Spectral analysis; Time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2000 10th European
  • Conference_Location
    Tampere, Finland
  • Print_ISBN
    978-952-1504-43-3
  • Type

    conf

  • Filename
    7075273