• DocumentCode
    483583
  • Title

    Adaptive array beam forming using a combined RLS-LMS algorithm

  • Author

    Srar, Jalal Abdulsayed ; Chung, Kah-Seng

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Curtin Univ. of Technol., Perth, WA
  • fYear
    2008
  • fDate
    14-16 Oct. 2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A new adaptive algorithm, called RLMS, which combines the use of recursive least square (RLS) and least mean square (LMS), is proposed for array beam forming. The convergence of the RLMS algorithm is analyzed, in terms of mean square error, in the presence of additive white Gaussian noise. Computer simulation results show that the convergence performance of RLMS is superior to either RLS or LMS operating on its own. Furthermore, the convergence of RLMS is quite insensitive to changes in either signal-to-noise ratio, or the initial value of the input correlation matrix for the RLS section, or the step size adopted for the LMS section.
  • Keywords
    AWGN; adaptive signal processing; array signal processing; convergence; matrix algebra; mean square error methods; recursive estimation; adaptive array beam forming; additive white Gaussian noise; combined RLS-LMS algorithm; convergence performance; correlation matrix; mean square error methods; recursive least square-least mean square algorithm; signal-to-noise ratio; Adaptive algorithm; Adaptive arrays; Additive white noise; Algorithm design and analysis; Computer simulation; Convergence; Least squares approximation; Least squares methods; Mean square error methods; Resonance light scattering; LMS algorithm; RLMS algorithm; RLS algorithm; adaptive array beam forming; array processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, 2008. APCC 2008. 14th Asia-Pacific Conference on
  • Conference_Location
    Tokyo
  • Print_ISBN
    978-4-88552-232-1
  • Electronic_ISBN
    978-4-88552-231-4
  • Type

    conf

  • Filename
    4773748