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Estimation of the acoustic wavenumbers presents great interests in shallow environ- ments. They provide relevant material to infer the sediment parameters. Using a horizontal ar- ray, the wavenumbers are obtained with usual spectral estimation methods in the spatial dimen- sion. The computation of the wavenumber spectra at several frequencies leads to a frequency- wavenumber (f−k) diagram, which is appropriate for the characterization of dispersive propa- gations. In this paper, a Compressed Sensing (CS) method is proposed to improve the separation of the wavenumbers. The CS approach is particularly relevant since only few modes are pro- pagating. However, at higher frequencies the number of propagating mode increases and the wavenumber separation becomes more difficult, especially when using short arrays. This paper introduces a wideband particle filtering (PF) algorithm for the wavenumber tracking. It takes advantage of the dispersion relation which is true in every waveguides. The consecutive use of CS and PF allows computing the f-k representation for array measurements that does not respect the usual requirements of array length. An application on the 32 sensor SHARK array of the SW06 campaign illustrates the whole methodology.
wavenumber, spectral estimation, particular filtering, compressed sensing.
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