• DocumentCode
    2079490
  • Title

    Sparse signal representation for MIMO radar imaging

  • Author

    Roberts, William ; Yardibi, Tarik ; Li, Jian ; Tan, Xing ; Stoica, Petre

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL
  • fYear
    2008
  • fDate
    26-29 Oct. 2008
  • Firstpage
    609
  • Lastpage
    613
  • Abstract
    MIMO radar can achieve superior performance over the conventional phased-array radar through waveform diversity. Considerations in transmit waveform and receive filter design are central to attaining improved performance through a MIMO system. Moreover, adaptive array techniques are needed to improve accuracy, resolution and to further provide interference suppression. Recently, the weighted least-squares based iterative adaptive approach (IAA), a non-parametric and user parameter-free method was shown to provide good performance for array processing. In this paper, we demonstrate how IAA can be extended for MIMO radar applications. Our simulations show that IAA outperforms other well-established methods in the field.
  • Keywords
    MIMO communication; phased array radar; radar imaging; MIMO; iterative adaptive approach; phased-array radar; radar imaging; sparse signal representation; waveform diversity; Adaptive arrays; Adaptive systems; Array signal processing; Filters; Interference suppression; Iterative methods; MIMO; Radar imaging; Signal representations; Signal resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2008 42nd Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA
  • ISSN
    1058-6393
  • Print_ISBN
    978-1-4244-2940-0
  • Electronic_ISBN
    1058-6393
  • Type

    conf

  • DOI
    10.1109/ACSSC.2008.5074478
  • Filename
    5074478