H. Gazzah, hgazzah@sharjah.ac.ae
Department of Electrical and Computer Eng.,
University of Sharjah, 27272 UAE
S.M. Jesus sjesus@ualg.pt
LARSys, University of Algarve,
Campus de Gambelas, PT-8005-139 Faro, Portugal.
Comments: download (pdf).
Ref.: IEEE Journal of Oceanic Engineering, vol.45(4), pp.1574-1582,
October 2020.
Abstract
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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