Improving Transient Signal Synthesis Through Noise Modeling and Noise Removal

Abstract

This thesis examines signal modeling techniques and their application to ambient ocean noise for purposes of noise removal and for generating realistic synthetic noise to add to synthetically generated transient signals. Higher order statistics of the noise are examined to test for Gaussianity. Stochastic approaches to AR, MA, and ARMA modeling are compared to see which technique yields the best synthetic noise. Results from the modeling process are used to develop a short-time Wiener filter which can be used to condition a real signal for further processing through effective noise removal.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1994
Accession Number
ADA281677

Entities

People

  • Kenneth L. Frack Jr

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Acoustics
  • Ambient Noise
  • Computational Complexity
  • Computers
  • Data Science
  • Electrical Engineering
  • Engineering
  • Frequency Bands
  • Gaussian Distributions
  • Information Processing
  • Information Science
  • Order Statistics
  • Random Variables
  • Signal Processing
  • Statistics
  • United States
  • United States Naval Academy

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Image Processing and Computer Vision.