In partial fulfillment of the requirements for the degree of
Doctor of Philosophy in Ocean Science & Engineering
In the
School of Earth and Atmospheric Science
Richard Xavier Touret
Will defend his dissertation
Acoustic Arrival Time Estimation in High Resolution Ocean Environments
November 22nd, 2024, 1:00pm EST
Room: MRDC 4211
Zoom Link: https://gatech.zoom.us/j/97637067680?pwd=SZzD8yyNfrykdfbsXO0oI54JjdnGQx.1
Passcode: 568659
Thesis Advisor:
Dr. Karim Sabra, Ph.D.
School of Mechanical Engineering
Georgia Institute of Technology
Committee Members:
Dr. Zhigang Peng, Ph.D.
School of Earth and Atmospheric Science
Georgia Institute of Technology
Dr. Julien Meaud, Ph.D.
School of Mechanical Engineering
Georgia Institute of Technology
Annalisa Bracco, Ph.D.
School of Earth and Atmospheric Science
Georgia Institute of Technology
Dr. Takamitsu Ito, Ph.D.
School of Earth and Atmospheric Science
Georgia Institute of Technology
ABSTRACT: Arrival times play a critical role in underwater acoustics, particularly in applications that require precise information about sound propagation through water. Accurate arrival times provide insights into the travel paths and speeds of acoustic waves, which are crucial for many relevant military and scientific applications. Underwater acoustic arrival times can be obtained experimentally in two ways: actively, by transmitting a known acoustic signal and matching it at the receiver; or passively through blind deconvolution techniques that analyze occurring sounds without knowledge of the impulse response. In active arrival estimation, a matched filter is typically employed to correlate a known source waveform with received signals, allowing for precise timing of specific arrivals. Conversely, with passive estimation, blind deconvolution relies on signal processing methods posed under strict assumptions to extract timing information. The current frameworks used to estimate these arrival structures typically combine experimentally measured acoustic signals in collaboration with numerical simulations (ideally performed in an accurate rendition of the ocean environment). To accomplish this in a satisfactory manner, it is required to accurately understand the relevant ocean environment with a high level of precision; and to utilize both an accurate signal estimation method and acoustic propagation model. These remain challenging, as commonly used blind deconvolution techniques do not account for realistic scenarios such as moving sources, and commonly used acoustic propagation models experience instability that scales with ocean precision. This doctoral project addresses these challenges by advancing acoustic modeling and signal estimation tools for complex ocean environments through three primary research objectives. First, a modification to the Ray-Based Blind Deconvolution (RBD) algorithm is presented to account for Doppler shifts, thereby enhancing the accuracy of arrival predictions in applications involving mobile sources. Second, the impact of ocean precision on acoustic accuracy is explored, specifically how mesoscale and submesoscale features in high-resolution ocean models introduce uncertainty in propagation estimates. Finally, optimizations to ray-tracing models for stabilizing acoustic Eigenray arrival predictions in dynamic are shown for range-dependent ocean environments. By comparing with the Parabolic Equation (PE) model, it is demonstrated that kernel smoothing and empirical orthogonal denoising of Sound Speed Profiles (SSPs) mitigate ray instability, enabling ray tracing with more viability and accuracy tool for these complex environments.