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Geoacoustic Inversion via Genetic Algorithm and Its Application to Manganese Sediment Identification
Authors:Woojae Seong  Cheolsoo Park
Institution:  a Department of Naval Architecture and Ocean Engineering, Seoul National University, Seoul, Korea.
Abstract:An acoustic inversion method using a wide-band signal and two near field receivers is proposed and applied to multiple layered seabed models including a manganese sediment. The inversion problem can be formulated into a probabilistic model comprised of signals, a forward model, and additive noise. The forward model simulates wide-band signals, such as chirp signals, and is chosen to be the source-waveletconvolution plane wave modeling method. The wavelet matching technique, using weighted least-squares fitting, estimates the sediment sound-speed and thickness on which determination of the possible numerical ranges for a priori uniform distribution is based. The genetic algorithm is applied to a global optimization problem to find a maximum a posteriori solution for determined a priori search space. Here the object function is defined by an L 2 norm of the difference between measured and modeled signals. Not only the marginal pdf but also its statistics are calculated by numerical evaluation of integrals using the samples selected during importance sampling process of the genetic algorithm.
Keywords:Geoacoustic  Inversion  Genetic  Algorithm  Chirp  Signals  Manganese  Crusts  Probabilistic  Model  Plane  Wave  Modeling  Wavelet  Matching  A  Posteriori  Solution
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