Abstract

We localized sound sources collected on a compact tetrahedral hydrophone array in a continental shelf environment south of Block Island, Rhode Island. The tetrahedral array of phones, 0.5 m on a side, was deployed to monitor the underwater sound of construction and operation of the first offshore wind farm in the United States. Signals from shipping and marine mammals, including fin whales, humpback whales, and right whales, were detected on the array. Directions of arrival (DOAs) for a number of signals were computed using a time difference of arrival technique. Given the DOAs, ranges were estimated using supervised machine learning techniques outlined by Niu et al. (JASA, 2017). The approach was tested using simulated data from Kraken assuming environmental information consistent with this continental shelf environment. Performance on signals from individual ships and marine mammals is presented. Ship localizations are compared to Automated Identification System (AIS) fixes. An error analysis is also presented. [Work supported by the Office of Naval Research and the Bureau of Ocean Energy Management.]

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