Invariant Mode Bayes Factor Active Sonar

Abstract

We propose to provide a suite of environmentally aware active sonar processors that exploit vertical arrival structure through environmental information in the form of invariant mode expansions of the Bayes Factor. These processors will optimally exploit environmental information such as sound speed structure, volume and surface reverberation information along with motion scenario information. Optimal fusion of information will improve active sonar systems. The Bayes Factor Active Sonar (BFAS) paradigm will be further explored and detection schemes will be developed that exploit the entire joint field of view in vertical angle, horizontal angle and delay through the lens of knowledge of the environment. Such prior environmental information is available and the Bayesian approach yields processing chains that optimally fuse environmental information with acoustic array observations.

Document Details

Document Type
DoD Grant Award
Publication Date
Nov 09, 2024
Source ID
N000142412763

Entities

People

  • Paul Gendron

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Massachusetts

Tags

Readers

  • Acoustical Oceanography.
  • Artificial Intelligence
  • Atmospheric Science/Meteorology

Technology Areas

  • AI & ML