title: Compressive beamforming.
abstract: Sound source localization with sensor arrays involves the estimation of the direction-of-arrival (DOA) from a limited number of observations. Compressive sensing (CS) solves such underdetermined problems achieving sparsity, thus improved resolution, and can be solved efficiently with convex optimization. The DOA estimation problem is formulated in the CS framework and it is shown that CS has superior performance compared to traditional DOA estimation methods especially under challenging scenarios such as coherent arrivals and single-snapshot data. An offset and resolution analysis is performed to indicate the limitations of CS. It is shown that the limitations are related to the beampattern, thus can be predicted. The high-resolution capabilities and the robustness of CS are demonstrated on experimental array data from ocean acoustic measurements for source tracking with single-snapshot data.
authors.affiliation: Scripps Institution of Oceanography, University of California San Diego, La Jolla, California 92093-0238.
authors.forename: Angeliki
authors.initials: A
authors.lastname: Xenaki
authors.affiliation: Scripps Institution of Oceanography, University of California San Diego, La Jolla, California 92093-0238.
authors.forename: Peter
authors.initials: P
authors.lastname: Gerstoft
authors.affiliation: Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, 2800 Denmark.
authors.forename: Klaus
authors.initials: K
authors.lastname: Mosegaard