Location, Tracking, and Classification of On-Ice and Underwater Noise Sources Using Machine Learning

Abstract

Changing Arctic ice conditions warrant new study of acoustic localization, tracking, and classification of anthropogenic sources, important for situational awareness in the ocean battlespace. The main objective of this work is to provide hands-on, militarily-relevant education opportunities for students in under-ice acoustics and machine learning. The second objective of this work is to advance the understanding of multi-modal acoustic localization, tracking, and classification in ice-covered, shallow-water zones using deep learning with acoustic vector sensor data.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 27, 2020
Source ID
N001741910004

Entities

People

  • Timothy C Havens

Organizations

  • Michigan Technological University
  • United States Navy

Tags

Readers

  • Oceanography.
  • Polar and Arctic Studies
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks