Wake acoustic analysis and image decomposition via beamforming of microphone signal projections on wavelet subspaces

Details

• Creators:
  Wassaf, Hadi ; Zhang, Yan ; Ibe, Oliver C.
• Corporate Creators:
  John A. Volpe National Transportation Systems Center (U.S.) ; Jet Propulsion Laboratory (U.S.) ; University of Massachusetts at Lowell
• Subject/TRT Terms:
  Mathematical Methods Phased Arrays Vortices Wakes Wavelets
• Publication/ Report Number:
  AIAA 2006-2536
• Resource Type:
  Proceedings
• Geographical Coverage:
  United States
• Corporate Publisher:
  American Institute of Aeronautics and Astronautics
• Abstract:
  This paper describes the integration of wavelet analysis and time-domain beamforming
  
  of microphone array output signals for analyzing the acoustic emissions from airplane
  
  generated wake vortices. This integrated process provides visual and quantitative
  
  simultaneous information about the wake signal composition and array resolution for a
  
  particular wavelet subspace during a time interval, T. In the results section, an example is
  
  given on how image processing algorithms might be used to automate the extraction of this
  
  information and select the wavelet subspaces from which to perform image reconstruction.
  
  This process begins with the projection of all the microphone signals on wavelet multiresolution
  
  subspaces. The projections of these signals on the same wavelet subspace or scale
  
  are then beamformed to produce an image of the wake corresponding to that particular
  
  scale. Therefore for each time interval T, the process produces a number of images equal to
  
  that of the wavelet scales. This is equivalent to a more conventional Fourier-based idea of
  
  filtering the microphone signals with band-pass filters having non-uniform bandwidths then
  
  beamform in different sub-bands, but offers greater flexibility and enhanced computational
  
  speed. Results from both approaches will be shown, which ultimately illustrate the
  
  advantages of wavelet analysis over that of the Fourier-based analysis. Amongst the
  
  advantages are the speed of the decomposition and ease of the image reconstruction from
  
  selected subspaces aided by the perfect reconstruction and orthogonality properties of
  
  wavelet analysis.
  
  
• Format:
  PDF
• Collection(s):
  Volpe Center
• Main Document Checksum:
  urn:sha-512:daaa500528c4f0be1d0d940e7837258a80deb0ac3e4650bf63069088ffb148f3e0f85f68faebe4e091c95d13311bcd83bf76ecf00bf5f473caebf2232ca717fe
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/8951/dot_8951_DS1.pdf
• File Type:
  [PDF - 403.64 KB ]