Underwater acoustic azimuth and elevation angle estimation using spatial invariance of two identically oriented vector hydrophones at unknown locations in impulsive noise

Abstract

This paper proposes a new underwater acoustic 2-D direction finding algorithm using two identically oriented vector hydrophones at unknown locations in non-Gaussian impulsive noise. The two applied vector hydrophones are four-component, orienting identically in space with arbitrarily and possibly unknown displacement. Each vector hydrophone has three spatially co-located but orthogonally oriented velocity hydrophones plus another pressure hydrophone. The proposed algorithm employs the spatial invariance between the two vector hydrophones, but requires no a priori information of vector hydrophones' spatial factors and impinging sources' temporal forms. We apply ESPRIT to estimate vector hydrophones manifold and then to pair the x-axis direction cosines with y-axis direction cosines automatically and yield azimuth and elevation angle estimates. We also consider the additive noise be non-Gaussian impulsive, which is often encountered in underwater acoustics applications. Two typical impulsive noise model, Gaussian-mixture noise and symmetric @a-stable (S@aS) noise models are adopted. Instead of using conventional second order correlation of array output data, we define the vector hydrophone array sign covariance matrix (VSCM) for Gaussian-mixture noise and vector hydrophone array fractional lower order moment (VFLOM) matrix for S@aS noise with 1<@a=<2. These defined matrices may readily substitute customary vector hydrophone array covariance matrix for 2-D direction finding in impulsive noise.