• Login
    View Item 
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Motion tomography performed by autonomous underwater vehicles

    Thumbnail
    View/Open
    OUERGHI-THESIS-2017.pdf (1.076Mb)
    Date
    2017-08-02
    Author
    Ouerghi, Meriam
    Metadata
    Show full item record
    Abstract
    Motion Tomography (MT) is a novel method to estimate an ambient flow field. Based on collective data obtained from the autonomous underwater vehicles (AUV), MT formulates a specific nonlinear system of equations as an inverse problem. In this thesis, we redesign the MT algorithm by using a local approximation of the gradient of AUV position. We establish a theoretical study of motion tomography (MT) problem, where we focus on the evolution of the AUV predicted trajectory, computed by the MT algorithm, to derive the MT error dynamics. A main result of this thesis illustrates a fundamental connection between the trajectory tracing mechanism and the flow update. This insight is not only relevant for proving the convergence of the MT algorithm, but provides a new perspective on inverse problems in general. To overcome the complexity of the underlying problem, we follow a systematic scheme: We start by analyzing one vehicle MT and then we enlarge the scope to multiple vehicle MT. Therein, we looked for an appropriate way to incorporate the collected data from AUVs and accounting for several reasons, discussed in this work, we focused on Motion Tomography Correction per Cycle (MTCC). We proved the convergence of the redesigned algorithm MTCC without imposing the Lipschitz continuity property. Furthermore, we improved the accuracy of ambient flow field estimation by extending the MT algorithm with second part. We modified the AUV predicted velocity so that the simulated final time converges to the measured travel time. Finally, the simulations are in good agreement with the theoretical study and underpin the derived conclusions.
    URI
    http://hdl.handle.net/1853/59185
    Collections
    • Georgia Tech Theses and Dissertations [23877]
    • School of Mechanical Engineering Theses and Dissertations [4086]

    Browse

    All of SMARTechCommunities & CollectionsDatesAuthorsTitlesSubjectsTypesThis CollectionDatesAuthorsTitlesSubjectsTypes

    My SMARTech

    Login

    Statistics

    View Usage StatisticsView Google Analytics Statistics
    facebook instagram twitter youtube
    • My Account
    • Contact us
    • Directory
    • Campus Map
    • Support/Give
    • Library Accessibility
      • About SMARTech
      • SMARTech Terms of Use
    Georgia Tech Library266 4th Street NW, Atlanta, GA 30332
    404.894.4500
    • Emergency Information
    • Legal and Privacy Information
    • Human Trafficking Notice
    • Accessibility
    • Accountability
    • Accreditation
    • Employment
    © 2020 Georgia Institute of Technology