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:
  • Wavelets
  • Phased arrays
  • Wakes
  • Vortices
  • Mathematical methods
• 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.
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• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/8951/dot_8951_DS1.pdf
• File Type:
  [PDF - 403.64 KB]
• Collection(s):
  Volpe Center
• Main Document Checksum:
  urn:sha-512:daaa500528c4f0be1d0d940e7837258a80deb0ac3e4650bf63069088ffb148f3e0f85f68faebe4e091c95d13311bcd83bf76ecf00bf5f473caebf2232ca717fe