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arxiv: 1712.02654 · v1 · pith:ENO2OOGAnew · submitted 2017-12-07 · 🧮 math.AP

Fast acoustic source imaging using multi-frequency sparse data

classification 🧮 math.AP
keywords datasourcemethodacousticfastfrequencyimagingmultiple
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We consider the acoustic source imaging problems using multiple frequency data. Using the data of one observation direction/point, we prove that some information (size and location) of the source support can be recovered. A non-iterative method is then proposed to image the source for the Helmholtz equation using multiple frequency far field data of one or several observation directions. The method is simple to implement and extremely fast since it only computes an indicator function on the interested domain using only matrix vector multiplications. Numerical examples are presented to validate the effectiveness of the method.

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  1. A parametric Bayesian level set approach for acoustic source identification using multiple frequency information

    math.NA 2019-07 unverdicted novelty 5.0

    Parametric Bayesian level set approach with radial basis expansion and Metropolis-Hastings sampling reconstructs acoustic sources from multiple frequency data, proving posterior well-posedness and showing competitive ...