Abstract
The application of compressive sensing to detect targets of interest could greatly impact future beamforming systems. Inevitably, at-sea data are contaminated with measured noise. When the ocean is stationary enough to form multiple snap-shots, a covariance matrix may be formed to mitigate noise. Results of compressive beamforming on a covariance matrix will be shown on at-sea measurements. Results will be compared with a robust adaptive beamformer and compressive beamformer. It will be shown that the dictionary of a compressive covariance beamformer goes as the number of measurements squared leading to a compromise between processor and array gain. [This work was supported by ONR.]
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