Sponsor
Portland State University. Department of Electrical and Computer Engineering
First Advisor
Martin Siderius
Date of Publication
Winter 3-20-2015
Document Type
Thesis
Degree Name
Master of Science (M.S.) in Electrical and Computer Engineering
Department
Electrical and Computer Engineering
Language
English
Subjects
Underwater acoustics -- Measurement -- Data processing, Signal processing -- Research, Interference (Sound) -- Research
DOI
10.15760/etd.2195
Physical Description
1 online resource (vi, 45 pages)
Abstract
Vertical line arrays (VLAs) deployed below the critical depth in the deep ocean can exploit reliable acoustic path (RAP) propagation, which provides low transmission loss (TL) for targets at moderate ranges, and increased TL for distant interferers. However, sound from nearby surface interferers also undergoes RAP propagation, and without horizontal aperture, a VLA cannot separate these interferers from submerged targets. A recent publication by McCargar and Zurk (2013) addressed this issue, presenting a transform-based method for passive, depth-based separation of signals received on deep VLAs based on the depth-dependent modulation caused by the interference between the direct and surface-reflected acoustic arrivals. This thesis expands on that work by quantifying the transform-based depth estimation method performance in terms of the resolution and ambiguity in the depth estimate. Then, the depth discrimination performance is quantified in terms of the number of VLA elements.
Rights
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Persistent Identifier
http://archives.pdx.edu/ds/psu/15180
Recommended Citation
Boyle, John K., "Performance Metrics for Depth-based Signal Separation Using Deep Vertical Line Arrays" (2015). Dissertations and Theses. Paper 2198.
https://doi.org/10.15760/etd.2195