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Efficient angular spectrum decomposition of acoustic sources. I. Theory.

D P Orofino1, P C Pedersen

  • 1Dept. of Electr. and Comput. Eng., Worcester Polytech. Inst., MA.

IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
|January 1, 1993
PubMed
Summary

This study introduces an efficient angular spectrum decomposition algorithm using 2-D FFT for acoustic fields. It enables faster source plane decomposition with an antialiasing method, optimizing accuracy and computational cost.

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Area of Science:

  • Acoustics
  • Numerical Methods
  • Signal Processing

Background:

  • Angular spectrum decomposition is crucial for analyzing acoustic fields.
  • Accurate decomposition requires careful consideration of sampling and discretization.
  • Existing methods can be computationally intensive, especially for complex transducer shapes.

Purpose of the Study:

  • To evaluate angular spectrum decomposition using 2-D FFT for plane wave analysis.
  • To develop an efficient algorithm for source plane decomposition of acoustic fields.
  • To propose an antialiasing method for improved discretization accuracy and reduced computational cost.

Main Methods:

  • Utilized two-dimensional Fast Fourier Transform (2-D FFT) for angular spectrum decomposition.
  • Developed an algorithm for decomposing normal velocity and pressure fields in the source plane.
  • Proposed an antialiasing algorithm to minimize sample points for a given accuracy.

Main Results:

  • The 2-D FFT-based algorithm efficiently decomposes acoustic fields in the source plane.
  • The proposed antialiasing algorithm reduces the number of required sample points.
  • Guidelines are provided for selecting sampling intervals and discretization sizes to balance accuracy and computational cost.

Conclusions:

  • The developed algorithm offers a computationally efficient approach to angular spectrum decomposition.
  • The antialiasing technique enhances the practicality of the method for various transducer shapes.
  • This work provides a framework for optimizing numerical accuracy and computational efficiency in acoustic field analysis.