Shallow Water MCM and ASW Using Off-Board, Autonomous Sensor Networks and Multistatic, Time-Reversal Acoustics

Abstract

To utilize high fidelity acoustic modeling of both scatterers and shallow-water environments to better understand and bound the limits of detectability for mine-like objects via autonomous networks of sensors. To conduct a series of realistic experiments using multiple sonar-equipped AUVs in shallow water and then cross-validate the results obtained with high precision modeling and visualization. To better understand the problems of cooperative autonomous vehicle interaction to define the base-line infrastructure requirements for cooperative detection, classification and navigation.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2007
Accession Number
ADA569083

Entities

People

  • David Battle
  • Henrik Schmidt

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Acoustics
  • Autonomous Vehicles
  • Classification
  • Data Sets
  • Detection
  • Detectors
  • Environment
  • Frequency
  • Measurement
  • Medium Frequency
  • Navigation
  • Networks
  • Scattering
  • Sensor Networks
  • Shallow Water
  • Three Dimensional
  • Water

Readers

  • Acoustical Oceanography.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control