Wavelet Digital Signal Processing of Undersea Acoustic Data

Abstract

Chirplet signal reconstruction algorithms have been developed using MATLAB. A Flexible Chirplet Transform algorithm has been developed. Building and implementation of chirplet reconstruction algorithms have been completed successfully. Feature extraction and noise removal for low frequency acoustic chirp signals have been completed using scalar wavelet, wavelet packet, multiwavelet, and chirplet and Fourier techniques. Comparison of these methods has been performed, and the results have been analyzed. Adaptive wavelet transform algorithms via lifting have been developed and are currently being used to design specific wavelet transform for low frequency broadband simulated chirp signals.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2002
Accession Number
ADA405774

Entities

People

  • George E. Ioup
  • Joseph S. Wheatley
  • Juliette W. Ioup

Organizations

  • University of New Orleans

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Abstracts
  • Acoustic Signals
  • Algorithms
  • Amplitude
  • Broadband
  • Classification
  • Detection
  • Digital Signal Processing
  • Extraction
  • Feature Extraction
  • Frequency
  • Maximum Likelihood Estimation
  • Noise
  • Removal
  • Signal Processing
  • Underwater Acoustics
  • Wavelet Transforms

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Image Processing and Computer Vision.

Technology Areas

  • AI & ML