• DocumentCode
    616676
  • Title

    Statistical modelling of measured automotive radar reflections

  • Author

    Buller, W. ; Wilson, Brian ; van Nieuwstadt, L. ; Ebling, J.

  • Author_Institution
    Michigan Tech Res. Inst. (MTRI), Michigan Technol. Univ., Ann Arbor, MI, USA
  • fYear
    2013
  • fDate
    6-9 May 2013
  • Firstpage
    349
  • Lastpage
    352
  • Abstract
    A statistical analysis was performed on measured radar reflections from a broad range of personal vehicle classes. The outcome of this study is two-fold: 1.) An improved understanding of the radar scattering components of automobiles, which informs the design of surrogate test targets for evaluating automotive pre-collision system (PCS) radars, and 2.) statistical models for evaluating surrogate targets and characterizing target models for PCS radar system designs. We examined the validity of two-parameter distribution models applied to measurements of subject vehicle´s radar cross-section (RCS) and found the Weibull distribution to be the best fit. In evaluating the goodness-of-fit of the Weibull distribution model, using the Kolmogorov-Smirnov test, we deem an acceptable fit between the model and the measured RCS data for our intended project outcome.
  • Keywords
    Weibull distribution; electromagnetic wave scattering; radar cross-sections; road vehicle radar; statistical analysis; Kolmogorov-Smirnov test; PCS radar system designs; PCS radars; RCS; Weibull distribution model; automobiles; automotive pre-collision system radars; measured automotive radar reflections; radar cross-section; radar scattering components; statistical analysis; statistical modelling; statistical models; target models; two-parameter distribution models; Automotive engineering; Data models; Radar cross-sections; Vehicles; Weibull distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference (I2MTC), 2013 IEEE International
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1091-5281
  • Print_ISBN
    978-1-4673-4621-4
  • Type

    conf

  • DOI
    10.1109/I2MTC.2013.6555438
  • Filename
    6555438