Optimization of linear and planar array geometries for unmanned underwater vehicle acoustic imaging techniques

Abstract

Unmanned underwater vehicles (UUVs) are becoming more prevalent in industrial and scientific applications. A wide range of designs is available and many platforms are highly configurable, resulting in an ever-changing acoustic profile. Changes in the UUV’s noise may affect onboard sensors and potentially disturb the environment. An acoustic source imaging process is under development to provide a detailed analysis of the UUV noise in a rapid-turnaround environment. Measurements from a hydrophone array in the geometric near field of a UUV may be input to an acoustic inverse method [e.g., generalized inverse beamforming (GINV) or statistically optimized near-field acoustical holography (SONAH)] to spatially separate noise components and ascertain their levels. However, source resolution and accuracy are highly dependent on array design. Results of a recent numerical case study are presented towards the optimization of linear and planar array geometries. The array geometry is iterated and tuned based on the resultant beamwidth, sidelobe levels, and source localization accuracy for a range of octave frequency bands and source locations. The optimization results provide insight into the critical design factors for acoustical imaging techniques, as well as a suitable array geometry for improved UUV acoustic imaging.