Long-Range Automatic Detection, Acoustic Signature Characterization and Bearing-Time Estimation of Multiple Ships with Coherent Hydrophone Array
Chenyang Zhu, Sai Geetha Seri, Hamed Mohebbi-Kalkhoran, Purnima Ratilal
Abstract
Three approaches for instantaneous wide-area analysis of ship-radiated underwater sound, each focusing on a different aspect of that sound, received on a large-aperture densely-sampled coherent hydrophone array have been developed. (i) Ship’s narrowband machinery tonal sound is analyzed via temporal coherence using Mean Magnitude-Squared Coherence (MMSC) calculations. (ii) Ship’s broadband amplitude-modulated cavitation noise is examined using Cyclic Spectral Coherence (CSC) analysis that provides estimates for propeller blade pass rotation frequency, shaft rotation frequency, and hence the number of propeller blades. (iii) Mean power spectral densities (PSD) averaged across broad bandwidths are calculated in order to detect acoustically energetic ships. Each of these techniques are applied after beamforming of the received acoustic signals on a coherent hydrophone array, leading to significantly enhanced signal-to-noise ratios for simultaneous detection, bearing-time estimation and acoustic signature characterization of multiple ships over continental-shelf scale regions. The approaches are illustrated with underwater recordings of a 160-element coherent hydrophone array for six ocean vessels, that are located at a variety of bearings and ranges out to 200 km from the array, in the Norwegian Sea in February 2014. The CSC approach is shown to also be useful for automatic detection and bearing-time estimation of repetitive marine mammal vocalizations, providing estimates for inter-pulse-train and inter-pulse intervals from CSC spectra cyclic fundamental and first recurring peak frequencies respectively.