An experiment to investigate aural classification of coherent-source active sonar data

Abstract

Active sonar performance is degraded by the presence of environmental clutter objects, which lead to false alarm echoes. Earlier research suggests that perceptual signal features similar to those employed in the human auditory system can be used to automatically discriminate between impulsive‐source target and clutter echoes, thereby improving sonar performance by reducing the number of false alarms [V.W. Young et al., Can. Acoust. 34(3), 50–51 (2006)]. The present work attempts to extend these findings to the realm of coherent‐source active sonar echoes. To this end, an experiment was conducted on the Malta Plateau using a cardioid towed‐array and broadband FM sweeps running from 500 Hz up to 3.5 kHz. The data set consists of hundreds of pulse‐compressed echoes from several targets, shipwrecks, and clutter objects. It includes both monostatic and bistatic echoes, as well as echoes recorded at different aspect angles and at different propagation ranges between roughly 5 km and 30 km. In this paper the experiment is reviewed and preliminary results are presented for an automatic classifier that employs features based on a simple auditory model.