Wide Area Detection and Identification of Underwater UXO Using Structural Acoustic Sensors

Abstract

This project explored the feasibility and advantages of applying the structural acoustic feature-based technique to the detection and identification of underwater unexploded ordnance (UXO) especially for buried targets. In the structural acoustic regime, the echoes are related to the vibrational dynamics of the object, and time-frequency features in the scattered echoes can be used to "fingerprint" the target. The research centered around (1) comprehensive state-of-the-art UXO scattering measurements in the NRL structural acoustic underwater laboratory free-field and sediment facilities and off the coast of Panama City, FL, using a rail-based robotic sonar system and (2) the application of time and frequency based numerical models. The structural acoustic approach to target detection and identification offers significant advantages over more conventional acoustic approaches which rely on the formation of high resolution images. These advantages include: diverse set of "fingerprints" leading to low false alarm rates; longer range operation leading to wide area coverage; and low frequency sediment penetration leading to buried target prosecution.

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Document Details

Document Type
Technical Report
Publication Date
Jul 08, 2011
Accession Number
ADA546324

Entities

People

  • A. Sarkissian
  • Brian H. Houston
  • D. Calvo
  • H. Simpson
  • J. A. Bucaro
  • L. Kraus
  • M. Saniga
  • Saikat Dey
  • T. Yoder
  • Z. Waters

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acoustic Detectors
  • Acoustic Propagation
  • Acoustic Properties
  • Acoustic Waves
  • Acoustics
  • Autonomous Underwater Vehicles
  • Computational Science
  • Detection
  • Detectors
  • Diffraction
  • Frequency Bands
  • Geometry
  • Machine Learning
  • Mortar Ammunition
  • Supervised Machine Learning
  • Three Dimensional
  • Two Dimensional

Readers

  • Acoustical Oceanography.
  • Military/Explosive Ordnance Disposal (EOD) Technology
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML
  • Autonomy