Compressive two-dimensional beamforming for localization of tip vortex cavitation

Abstract

Noises induced by propeller tip vortex cavitation (TVC) have sparse sources near the propeller tip. Localization of these noise sources with sensor arrays involves the direction-of-arrival (DOA) estimation. Provided the noise sources are sparsely located, compressive sensing (CS) is used for two-dimensional (2-D) DOA estimation, which estimates both azimuth and elevation angles of the sources. With a planar array configuration, the 2-D DOA estimation problem is formulated in the CS framework and CS has shown less ambiguity and higher resolution capabilities compared to traditional DOA estimation schemes even under a single snapshot data. The superior performance of CS is demonstrated on experimental data from cavitation tunnel experiments. Two experimental data are considered. For the first experiment with one known source location, the true DOA has been estimated using CS. The second case involves initially intended TVC noises, and CS has estimated DOAs near the upper downstream area of the propeller, where TVC noises are generally generated.