Publications in Scientific Journals:
P. Gerstoft, A. Xenaki, C. Mecklenbräuker:
"Multiple and single snapshot compressive beamforming";
Journal of the Acoustical Society of America,
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
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Electronic version of the publication:
Project Head Christoph Mecklenbräuker:
Kompression des rückgemeldeten Kanalzustands für zeitvariante MIMO Kanäle
Created from the Publication Database of the Vienna University of Technology.