Date of Award
Fall 12-2018
Degree Type
Thesis
Degree Name
M.S.
Degree Program
Applied Physics
Department
Physics
Major Professor
Dr. Juliette Ioup
Second Advisor
Dr. Stan Chin-Bing
Third Advisor
Dr. Paul Elmore
Fourth Advisor
Chris Mire
Abstract
A challenge in Underwater Acoustics is identifying the independent variables associated with an environment’s ambient noise. A strict definition of ambient noise would focus on non-transient signatures and exclude transient impacts from marine mammals, pelagic fish species, man-made sources, or weather events such as precipitation or wind speeds. Recognizing transient signatures in acoustic spectra is an essential element for providing environmental intelligence to the U.S. Navy, specifically the acoustic signatures from meteorological events. While weather event detection in acoustic spectra has been shown in previous studies, leveraging these concepts via U.S. Navy assets is largely an unknown. Environmental intelligence collection can be improved by detecting precipitation events and establishing wind velocities with acoustic signatures. This will further improve meteorological models by enabling validation from both manned and unmanned sub-surface assets.
Recommended Citation
Kuhner, Joseph T., "Automating the Detection of Precipitation and Wind Characteristics in Navy Ocean Acoustic Data" (2018). University of New Orleans Theses and Dissertations. 2567.
https://scholarworks.uno.edu/td/2567
Rights
The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.