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P. Gerstoft, A. Xenaki, C. Mecklenbräuker:
"Multiple and single snapshot compressive beamforming";
Journal of the Acoustical Society of America, 138 (2015), 4; 2003 - 2014.

For a sound field observed on a sensor array, compressive sensing (CS) reconstructs the direction of arrival (DOA) of multiple sources using a sparsity constraint. The DOA estimation is posed as an underdetermined problem by expressing the acoustic pressure at each sensor as a phase-lagged superposition of source amplitudes at all hypothetical DOAs. Regularizing with an l1 -norm constraint renders the problem solvable with convex optimization, and promoting sparsity gives high-resolution DOA maps. Here the sparse source distribution is derived using maximum a posteriori estimates for both single and multiple snapshots. CS does not require inversion of the data covariance matrix and thus works well even for a single snapshot where it gives higher resolution than conventional beamforming. For multiple snapshots, CS outperforms conventional high-resolution methods even with coherent arrivals and at low signal-to-noise ratio. The superior resolution of CS is demonstrated with vertical array data from the SWellEx96 experiment for coherent multi-paths.

CS, compressed sensing, beamforming, sparse recovery, multipath propagation

http://dx.doi.org/10.1121/1.4929941

http://scitation.aip.org/content/asa/journal/jasa/138/4/10.1121/1.4929941

Project Head Christoph Mecklenbräuker:
Kompression des rückgemeldeten Kanalzustands für zeitvariante MIMO Kanäle