Poole
Travis L.
Poole
Travis L.
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ThesisGeoacoustic inversion by mode amplitude perturbation(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2007-02) Poole, Travis L.This thesis introduces an algorithm for inverting for the geoacoustic properties of the seafloor in shallow water. The input data required by the algorithm are estimates of the amplitudes of the normal modes excited by a low-frequency pure-tone sound source, and estimates of the water column sound speed profiles at the source and receiver positions. The algorithm makes use of perturbation results, and computes the small correction to an estimated background profile that is necessary to reproduce the measured mode amplitudes. Range-dependent waveguide properties can be inverted for so long as they vary slowly enough in range that the adiabatic approximation is valid. The thesis also presents an estimator which can be used to obtain the input data for the inversion algorithm from pressure measurements made on a vertical line array (VLA). The estimator is an Extended Kalman Filter (EKF), which treats the mode amplitudes and eigenvalues as state variables. Numerous synthetic and real-data examples of both the inversion algorithm and the EKF estimator are provided. The inversion algorithm is similar to eigenvalue perturbation methods, and the thesis also presents a combination mode amplitude/eigenvalue inversion algorithm, which combines the advantages of the two techniques.
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ArticleGeoacoustic inversion by mode amplitude perturbation(Acoustical Society of America, 2008-02) Poole, Travis L. ; Frisk, George V. ; Lynch, James F. ; Pierce, Allan D.This paper introduces a perturbative inversion algorithm for determining sea floor acoustic properties, which uses modal amplitudes as input data. Perturbative inverse methods have been used in the past to estimate bottom acoustic properties in sediments, but up to this point these methods have used only the modal eigenvalues as input data. As with previous perturbative inversion methods, the one developed in this paper solves the nonlinear inverse problem using a series of approximate, linear steps. Examples of the method applied to synthetic and experimental data are provided to demonstrate the method's feasibility. Finally, it is shown that modal eigenvalue and amplitude perturbation can be combined into a single inversion algorithm that uses all of the potentially available modal data.