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Information content of ship noise on a drifting volumetric array for passive environmental sensing

TitleInformation content of ship noise on a drifting volumetric array for passive environmental sensing
Publication TypeJournal Article
Year of Publication2020
AuthorsKubicko J.S, Verlinden C.M, Sarkar J., Sabra KG, Nichols B.V, Martin J.S, Fagan A.I
Volume45
Pagination607-630
Date Published2020/04
Type of ArticleArticle
ISBN Number0364-9059
Accession NumberWOS:000529928200023
KeywordsAcoustic; acoustics; drifting; Engineering; estimation; frequency ambient noise; fundamental limitations; inversion; Marine vehicles; ocean acoustic tomography; oceanography; oceans; receivers; Sea measurements; shallow; Sonar equipment; sound; time-delay; tomography; water; wave
Abstract

This study investigates the information content of ship noise received on a drifting volumetric array of hydrophones in shallow water marine environments for the purposes of conducting acoustic thermometry or other environmental inversions. Passive inversions for physical oceanographic parameters are conducted using travel time differences, determined by cross-correlating ship noise received on hydrophones suspended beneath drifting buoys. Ships are tracked using the automatic identification system. Information content gained from the inversion is assessed using traditional a posteriori error analysis. Numerical simulations using a standard normal mode propagation model are used to test limitations of the proposed approach with respect to frequency band, drifting receiver configuration, precision, and accuracy of the inversion results, along with sensitivity to environmental and position mismatch. Performance predictions using this model are compared with results from a field experiment using at-sea data collected off the coast of New London, CT, USA, in Long Island Sound. Information gathered using passive acoustic inversion methods on drifting arrays can be used to constrain general circulation models, in coastal environments, where ship noise is ubiquitous, environmental data is sparse, and the oceanography is dynamic and important for understanding large-scale ocean processes.

DOI10.1109/joe.2018.2877873
Student Publication: 
No
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