Machine Learning and Sparse Processing in Support of Ocean Environmental Inversion
Abstract
Our objectives include the development of new ocean environmental inversion methods, their use in the analysis of shallow water experimental data, and evaluation of geoacoustic model parameter uncertainties including the mapping of these uncertainties through to system performance uncertainties. Of specific technical interest are the development of methods to estimate and track environmental parameters using: (1) sparse sampling, (2) machine learning, (3) ambient noise, and (4) analyze data from recent ocean acoustics experiments.This abstract is approved for public release.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 21, 2023
- Source ID
- N000142412016
Entities
People
- Peter Gerstoft
Organizations
- Office of Naval Research
- United States Navy
- University of California, San Diego