• DocumentCode
    22331
  • Title

    Sparse Array Design for Wideband Beamforming With Reduced Complexity in Tapped Delay-Lines

  • Author

    Hawes, Matthew B. ; Wei Liu

  • Author_Institution
    Dept. of Electron. & Electr. Eng., Univ. of Sheffield, Sheffield, UK
  • Volume
    22
  • Issue
    8
  • fYear
    2014
  • fDate
    Aug. 2014
  • Firstpage
    1236
  • Lastpage
    1247
  • Abstract
    Sparse wideband array design for sensor location optimization is highly nonlinear and it is traditionally solved by genetic algorithms (GAs) or other similar optimization methods. This is an extremely time-consuming process and an optimum solution is not always guaranteed. In this work, this problem is studied from the viewpoint of compressive sensing (CS). Although there have been CS-based methods proposed for the design of sparse narrowband arrays, its extension to the wideband case is not straightforward, as there are multiple coefficients associated with each sensor and they have to be simultaneously minimized in order to discard the corresponding sensor locations. At first, sensor location optimization for both general wideband beamforming and frequency invariant beamforming is considered. Then, sparsity in the tapped delay-line (TDL) coefficients associated with each sensor is considered in order to reduce the implementation complexity of each TDL. Finally, design of robust wideband arrays against norm-bounded steering vector errors is addressed. Design examples are provided to verify the effectiveness of the proposed methods, with comparisons drawn with a GA-based design method.
  • Keywords
    array signal processing; compressed sensing; delay lines; genetic algorithms; CS-based methods; GA-based design method; TDL coefficients; compressive sensing; frequency invariant beamforming; genetic algorithms; norm-bounded steering vector errors; optimization methods; reduced complexity; sensor location optimization; sparse narrowband array design; sparse wideband array design; tapped delay-lines; wideband beamforming; Array signal processing; Arrays; Complexity theory; Minimization; Robustness; Vectors; Wideband; Compressive sensing; frequency invariant beamforming; implementation complexity; robust beamforming; sparse array; wideband beamforming;
  • fLanguage
    English
  • Journal_Title
    Audio, Speech, and Language Processing, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    2329-9290
  • Type

    jour

  • DOI
    10.1109/TASLP.2014.2327298
  • Filename
    6822510