Researchers: Reverberation Experiment

DJ Tang

Senior Principal Oceanographer

Acoustics Department

APL-UW

Todd Hefner

Senior Principal Physicist

Acoustics Department

APL-UW

Peter Dahl

Senior Principal Engineer

Acoustics Department

APL-UW

Professor, Mechanical Engineering

Jie Yang

Senior Physicist

Acoustics Department

APL-UW

Eric Thorsos

Sr. Principal Physicist--Retiree

Acoustics Department

APL-UW

Affiliate Associate Professor, Electrical Engineering

Researchers: Target Scattering Experiment

Kevin Williams

Liaison of SEG

Senior Principal Physicist

Acoustics Department

APL-UW

Associate Professor, Oceanography

Steve Kargl

Senior Principal Physicist

Acoustics Department

APL-UW

Aubrey Espana

Senior Physicist

Acoustics Department

APL-UW

Funding

ONR

SERDP

TREX13

Target and Reverberation Experiment 2013

We’re trying to provide the database of various types of targets you could be potentially looking for out there in the ocean.

The goal is to model target acoustic responses in real-life scenarios and, in turn, improve Navy sonar’s ability to detect and classify underwater hazards.

TREX13 is a large-scale, collaborative ocean acoustics experiment supported by both the U.S. Office of Naval Research (ONR) and the Strategic Environmental Research and Development Program (SERDP).

The experiment will take place in the Gulf of Mexico near Panama City Beach, Forida in the spring of 2013 and will involve researchers from both the United States and Canada.

The two main components of the experiment are:

  • to measure mid-frequency reverberation in a shallow water environment
  • to detect and classify unexploded ordnance and mine-like targets on the seafloor using synthetic aperture sonar

Horizontal line array deployed with mid-frequency source

Goals

Reverberation Approach

Target Scattering Approach

  • Measure mid-frequency (1–10 kHz) shallow water reverberation under both winter (adiabatic sound speed profile) and summer (seasonal thermocline) conditions with full companion environmental measurements so model/data can be compared without ambiguity. Included in this goal is to make statistical estimates of the uncertainties associated with all the environmental conditions
  • Complement the reverberation measurements with simultaneous measurements of waveguide propagation, forward scatter, and direct backscatter
  • Investigate the use of broadband sonar in the detection, classification, and identification of underwater munitions and mine-like targets near a water-sediment interface
  • Determine and understand the ocean waveguide physics to and from a target at ranges of up to three water depths in order to model its effect on the target’s acoustic signature

By reducing the water depth to 20 m, the range at which the sound field is dominated by small grazing angle propagation and scattering is shorter than at deeper depths. Therefore, environmental measurements can be limited to a smaller area. This area will be further limited by using bottom-mounted horizontal receive arrays, so that only a 5 degree wedge-shaped ocean needs to be measured for environmental support.

To properly model reverberation, both propagation (including forward scatter) and backscatter must be measured and understood. The reverberation organically integrates many shallow water acoustics issues under one theme, providing a scenario where the various shallow water problems can be evaluated comprehensively.

This research is an extension of work that measured acoustic responses from a collection of underwater targets in a fresh-water pond with a flat sandy bottom and compared some of those measurements to finite-element model predictions. This effort will collect additional acoustic data from an extended inventory of targets in an oceanic environment.

Data-model comparisons will form the basis of classification schemes to discriminate targets from nearby clutter. A central hypothesis is that the environment and the geometry within that environment can alter an acoustic response of a target, so the target-in-the-environment must be taken into account during the development of robust detection, classification, and identification strategies.

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