• Title of article

    Adaptive beamforming of a towed array during a turn

  • Author/Authors

    W.A.، Kuperman, نويسنده , , W.S.، Hodgkiss, نويسنده , , P.، Gerstoft, نويسنده , , Song، Heechun نويسنده , , P.L.، Nielsen, نويسنده , , M.، Siderius, نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2003
  • Pages
    -43
  • From page
    44
  • To page
    0
  • Abstract
    During maneuvering, towed array beamforming degrades if a straight array is assumed. This is especially true for high-resolution adaptive beamforming. It is experimentally demonstrated that adaptive beamforming is feasible on a turning array, provided that array shape is estimated. The array shape can be inferred solely from the coordinates of the tow vesselʹs Global Positioning System (GPS) without any instrumentation in the array. Based on estimated array shape from the GPS, both the conventional beamformer and the white noise constrained (WNC) adaptive beamformer are shown to track the source well during a turn. When calculating the weight vector in the WNC approach, a matrix inversion of the cross-spectral density matrix is involved. This matrix inversion can be stabilized by averaging the cross-spectral density matrix over neighboring frequencies. The proposed algorithms have been tested on real data with the tow-vessel making 45 degree turns with a 500-m curvature radius. While turning, the improvement in performance over the assumption of a straight array geometry was up to 5 dB for the conventional beamformer and considerably larger for the WNC adaptive beamformer.
  • Keywords
    Learning capability , neural-network modularity , Storage capacity , two-hidden-layer feedforward networks (TLFNs)
  • Journal title
    IEEE Journal of Oceanic Engineering
  • Serial Year
    2003
  • Journal title
    IEEE Journal of Oceanic Engineering
  • Record number

    78938