In-situ characterization of sea state with improved navigation on an Autonomous Underwater Glider

Submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022. This thesis presents an Autonomous Underwater Glider (AUG) architecture with im...

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Bibliographic Details
Main Author: Burgess, Gregory A.
Format: Thesis
Language:English
Published: Massachusetts Institute of Technology and Woods Hole Oceanographic Institution 2022
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Online Access:https://hdl.handle.net/1912/29238
Description
Summary:Submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022. This thesis presents an Autonomous Underwater Glider (AUG) architecture with improved onboard navigation and acoustics-based sensing intended to enable basin-scale unattended surveys of our Earth’s most remote oceans. Traditional AUGs have long-been an important platform for oceanographic surveys due to their high endurance and autonomy, yet lack the operational flexibility to operate in many regions of scientific interest and the sensing capability to capture scientific data at the air-sea interface. Particularly of interest is the marginal ice zone (MIZ) in the Arctic and the Southern Ocean, as both are vitally important to understanding global climate trends, yet prohibitively expensive to persistently monitor with support vessels. To fill this observational gap, the sensing, navigation, and adaptability of AUGs must be improved. This is possible by employing onboard acoustic sensing for sea state observation and navigation, as well as incorporating vehicle improvements targeting maneuverability and intelligent adaptability to evolving environmental states. To enable persistent monitoring of both the water-column and air-sea interface, this thesis proposes an improved vehicle architecture for a more capable AUG, a real-time DVLaided navigation process that leverages ocean current sensing to limit localization error, and a subsea acoustics-based sea state characterization method capable of analyzing wave spectra under-ice and with zero surface expression. These methods are evaluated with respect to extensive laboratory experiments and field data collected during in-situ implementation. Support for this research was provided through grants from the National Science Foundation (NSF) Navigating the New Arctic Grant (NNA #1839063) and the National Ocean Partnership Program (NOPP) Enhanced ...