Remote Sediment Property Estimation from Chirp Data Collected During the Geoclutter Experiment

Abstract

The long term research objective is to develop a cost effective technique for mapping the top 20 meters of sediment properties using acoustic remote sensing. In previous years, a chirp sonar was developed to provide quantitative, wideband reflection measurements of the seabed with a vertical resolution of 10 cm. Neural network and fuzzy logic techniques have been used to automatically detect subsurface layer interfaces and to find the boundaries between sediment layers. Signal processing techniques were developed to estimate vertical profiles of impedance, attenuation and volume scattering coefficients. The procedures for remotely estimating sediment properties are being verified using core data and insitu measurements. New signal processing techniques have been developed that allow several sources transmitting simultaneously in different bands to build a wideband FM pulse in the far field. That wideband data is being used to improve the accuracy of the remote acoustic sediment property prediction procedures.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2002
Accession Number
ADA629012

Entities

People

  • Steven G. Schock

Organizations

  • Florida Atlantic University

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Acoustic Impedance
  • Acoustic Properties
  • Acoustic Velocity
  • Attenuation
  • Chirp Sonar
  • Far Field
  • Fuzzy Logic
  • Impedance
  • Measurement
  • Neural Networks
  • Physical Properties
  • Reflection
  • Remote Sensing
  • Scattering
  • Signal Processing
  • Sonar

Readers

  • Acoustical Oceanography.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks