Machine Learning and Artificial Intelligence for Acoustic Environmental Characterization and Sound Propagation Physics Analysis
Abstract
This proposal outlines a comprehensive study leveraging Machine Learning (ML) and Artificial Intelligence (AI) techniques to advance acoustic environmental characterization and sound propagation physics analysis in complex marine settings, particularly focusing on challenging environments like the Arctic, Gulf Stream, and offshore seamounts. The project aims to integrate ML with physical models to enhance undersea monitoring, characterize environmental soundscapes, and address discrepancies between acoustic propagation model predictions and observations using data-driven techniques.The work will encompass developing Bayesian models for environmental perturbation methods, enhancing acoustic signal processing, and improving sound propagation modeling. Simulated and experimental datawill be used to validate the proposed models and algorithms, leveraging data from various oceanographic experiments. Improved models and algorithms will lead to better undersea domain awareness, environmental estimation, and autonomous vehicle navigation, all of which have naval relevance in challenging and dynamic ocean environments.This abstract is approved for public release.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 08, 2024
- Source ID
- N000142412401
Entities
People
- William F. Jenkins
Organizations
- Office of Naval Research
- United States Navy
- University of California, San Diego