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Closed-Form Estimation of Normal Modes from a Partially Sampled Water Column

H. Gazzah,
Department of Electrical and Computer Eng.,
University of Sharjah, 27272 UAE
S.M. Jesus
LARSys, University of Algarve,
Campus de Gambelas, PT-8005-139 Faro, Portugal.

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Ref.: IEEE Journal of Oceanic Engineering, vol.45(4), pp.1574-1582, October 2020.

The output of a vertical linear array is used to infer about the parameters of the normal mode model that describes acoustic propagation in a shallow water. Often, singular vector decomposition is performed on the data and estimates are obtained of the model parameters. Such subspace algorithms deliver the exact modal functions only if the array is covering the total water column. We prove that this very restrictive requirement can be relaxed if two hydrophone arrays are used to sense an array of monochromatic sources, with arrays covering sparsely and partially the water column. Estimates of both the modal functions and the wavenumbers are obtained in a fully-automatic and search-free manner, under no restrictive condition. This methods compares advantageously to both existing subspace techniques that require dense sampling of the full water column, and to transform-domain techniques that require impulsive sources. With two (eigen and singular) vector decompositions, the proposed technique has the complexity of a regular subspace algorithm

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