Multiple snapshot compressive beamforming

Abstract

For sound fields observed on an array, compressive sensing (CS) reconstructs the multiple source signals at unknown directions-of-arrival (DOAs) using a sparsity constraint. The DOA estimation is posed as an underdetermined problem expressing the field at each sensor as a phase-lagged superposition of source amplitudes at all hypothetical DOAs. CS is applicable even for a single observation snapshot achieving a 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.