• DocumentCode
    251995
  • Title

    Frequency-dependent power amplifier modeling and correction for distortion in wideband radar transmissions

  • Author

    Dunn, Z. ; Yeary, Mark ; Fulton, Caleb

  • Author_Institution
    Adv. Radar Res. Center, Univ. of Oklahoma, Norman, OK, USA
  • fYear
    2014
  • fDate
    3-6 Aug. 2014
  • Firstpage
    61
  • Lastpage
    64
  • Abstract
    This paper presents initial results on utilizing the Volterra series, more specifically the Memory Polynomial model subset of the Volterra series, to model the power and frequency dependent non-linear distortion of a physical power amplifier. This modeling technique is also used to create the necessary digital predistortion so that, when used in series with the same modeled high power amplifier, the overall system acts solely as a linear function of input power within a given bandwidth. This amplifier modeling and associated digital predistortion are especially useful in wideband radar applications, where digital predistortion allows the amplifier to operate at its highest power added efficiency by operating in its compression region while still behaving linearly. As a result, wideband radar waveforms can be generated at high fidelity, maximizing transmission power with the given equipment while maintaining low range sidelobes. The results section of this paper reports preliminary findings.
  • Keywords
    Volterra series; power amplifiers; radar applications; Volterra series; compression region; digital predistortion; frequency dependent nonlinear distortion; high power amplifier; linear function; memory polynomial model subset; modeling technique; physical power amplifier; power added efficiency; power dependent nonlinear distortion; wideband radar transmissions; Arrays; Calibration; Computational modeling; Delays; Predistortion; Radar; Radar antennas;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (MWSCAS), 2014 IEEE 57th International Midwest Symposium on
  • Conference_Location
    College Station, TX
  • ISSN
    1548-3746
  • Print_ISBN
    978-1-4799-4134-6
  • Type

    conf

  • DOI
    10.1109/MWSCAS.2014.6908352
  • Filename
    6908352