• DocumentCode
    148872
  • Title

    Adaptive re-weighting homotopy for sparse beamforming

  • Author

    Neto, Fernando G. A. ; Nascimento, Vitor H. ; Zakharov, Yuriy V. ; de Lamare, Rodrigo C.

  • Author_Institution
    Escola Politec., Univ. of Sao Paulo, Sao Paulo, Brazil
  • fYear
    2014
  • fDate
    1-5 Sept. 2014
  • Firstpage
    1287
  • Lastpage
    1291
  • Abstract
    In this paper, a complex adaptive re-weighting algorithm based on the homotopy technique is developed and used for beamforming. A multi-candidate scheme is also proposed and incorporated into the adaptive re-weighting homotopy algorithm to choose the regularization factor and improve the signal-to-interference plus noise (SINR) performance. The proposed algorithm is used to minimize the degradation caused by sparsity in arrays with faulty sensors, or when the required degrees of freedom to suppress interference is significantly less than the number of sensors. Simulations illustrate the algorithm´s performance.
  • Keywords
    array signal processing; interference suppression; sensors; SINR performance; adaptive reweighting homotopy algorithm; complex adaptive reweighting algorithm; degree of freedom; faulty sensors; interference suppression; multicandidate scheme; regularization factor; signal-to-interference plus noise performance; sparse beamforming; Array signal processing; Interference; Sensor arrays; Signal processing algorithms; Signal to noise ratio; Vectors; Multi-candidate re-weighting homotopy; adaptive algorithms; beamforming;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
  • Conference_Location
    Lisbon
  • Type

    conf

  • Filename
    6952457