Synoptic Signal Processing to Characterize the Highly Variable Arctic Waveguide
Abstract
Acoustic signal processing and data analyses are proposed to explore three research thrusts which strengthen the link between physi"cal oceanography and acoustic propagation in a highly dynamic, Arctic waveguide. This effort seeks to estimate geoacoustical parameters in a fluctuating ocean medium, to utilize machine learning algorithms to filter acoustic array data for the purpose of investigating ambient noise directionality, and to explore the predictive acoustic capability of an adjoint regional ocean model. This proposal leverages a large scale data set resulting from the Office of Naval Research (ONR) sponsored 2016-2017 Canada Basin Acoustic Propagation Experiment (CANAPE). This yearlong data set contains synoptic acoustic, oceanographic, and environmental measurements design"ed to characterize the Arctic waveguide in the Beaufort Gyre and on the Chukchi Shelf.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 26, 2019
- Source ID
- N000141912721
Entities
People
- Jason D Sagers
Organizations
- Office of Naval Research
- United States Navy
- University of Texas at Austin