Complex Cepstrum Processing of Digitized Transient Calibration Data for Removal of Echoes.

Abstract

The complex cepstrum technique was investigated for possible use in removing echoes casued by early reflections when low-frequency, peaked-response transducers are calibrated with transient signals. The calibration environment permits a high signal-to-noise ratio and a free choice of input waveforms, both of which are advantages in complex cepstrum processing. The proper method of computation with this technique is discussed in detail. Cepstrum filtering methods are discussed. Synthetic measurement data produced by a J9 projector driven with a damped sinusoidal pulse and a pressure-release reflection are shown, and real measurement data from a low-frequency line array driven by a single-cycle sinusoid with complex surface and bottom reflections are also shown. In both the synthetic and the real data, the echoes were successfully removed using the complex cepstrum technique. Data were digitized directly and stored on digital magnetic tape. Oversampling was reduced by sifting to achieve the correct sampling rate required by the complex cepstrum method. The results indicate that echo removal performed by complex cepstrum processing can be accurate enough to have potential usefulness in calibration procedures. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 1977
Accession Number
ADA047414

Entities

People

  • Lynn B. Poche Jr.

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Calibration
  • Cepstrum Technique
  • Comb Filters
  • Computations
  • Computer Programs
  • Computers
  • Filters
  • Filtration
  • Frequency
  • Interpolation
  • Measurement
  • Military Research
  • Procedures (Computers)
  • Transducers
  • Underwater Sound
  • Waveforms
  • Waves

Readers

  • Acoustical Oceanography.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Image Processing and Computer Vision.