Two‐dimensional speed and depth filtering applied to shallow water matched‐field detection.

Abstract

Passive acoustic sonars have difficulty in detecting quiet sources in noisy shallow‐water environments. The standard approach to improve detection is to use a large aperture linear array of horizontally distributed hydrophones and azimuthal processing to increase the signal‐to‐noise ratio (SNR) through beamforming. A newer approach is to exploit the acoustic interference of normal modes in shallow water and apply matched‐field (model‐to‐data) correlation techniques to estimate source locations in depth and range using signals received on a linear vertical array. These localization techniques are not designed for detection of quiet targets and some applications preclude the use of vertical arrays. This work examines the utility of matched‐field processing on linear and planar horizontal arrays on the ocean bottom in shallow water. A speed and depth filter to eliminate high‐speed surface targets is applied. A track‐before‐detect strategy to convert matched‐field localizations into source detections in various physical and acoustic environments is utilized. We search for submerged targets at constant speed, constant depth, and linearly changing depth. We show the advantages of planar compared to linear arrays to discriminate submerged from surface sources as a function of SNR. [Work sponsored by QNA.]