Grid-free compressive beamforming

Angeliki Xenaki; Peter Gerstoft

doi:10.1121/1.4916269

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arXiv · 1504.01662

Grid-free compressive beamforming

Angeliki Xenaki·Peter Gerstoft

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Abstract

The direction-of-arrival (DOA) estimation problem involves the localization of a few sources from a limited number of observations on an array of sensors, thus it can be formulated as a sparse signal reconstruction problem and solved efficiently with compressive sensing (CS) to achieve high-resolution imaging. On a discrete angular grid, the CS reconstruction degrades due to basis mismatch when the DOAs do not coincide with the angular directions on the grid. To overcome this limitation, a continuous formulation of the DOA problem is employed and an optimization procedure is introduced, which promotes sparsity on a continuous optimization variable. The DOA estimation problem with infinitely many unknowns, i.e., source locations and amplitudes, is solved over a few optimization variables with semidefinite programming. The grid-free CS reconstruction provides high-resolution imaging even with non-uniform arrays, single-snapshot data and under noisy conditions as demonstrated on experimental towed array data.

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Angeliki Xenaki, Peter Gerstoft. 2015-03-12. Grid-free compressive beamforming. https://doi.org/10.1121/1.4916269

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