In this thesis, we develop the basics of the Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) technique for the instantaneous continental-shelf scale detection, localization and species classification of marine mammal vocalizations. POAWRS uses a large-aperture, densely sampled coherent hydrophone array system with orders of magnitude higher array gain to enhance signal-to-noise ratios (SNR) by coherent beamforming, enabling detection of underwater acoustic signals either two orders of magnitude more distant in range or lower in SNR than a single hydrophone.
The ability to employ coherent spatial processing of signals with the POAWRS technology significantly improves areal coverage, enabling detection of oceanic sound sources over instantaneous wide areas spanning 100 km or more in diameter. The POAWRS approach was applied to analyze marine mammal vocalizations from diverse species received on a 160-element Office Naval Research Five Octave Research Array (ONR-FORA) deployed during their feeding season in Fall 2006 in the Gulf of Maine. The species-dependent temporal-spatial distribution of marine mammal vocalizations and correlation to the prey fish distributions have been determined.
Furthermore, the probability of detection regions, source level distributions and pulse compression gains of the vocalization signals from diverse marine mammal species have been estimated. We also develop an approach for enhancing the angular resolution and improving bearing estimates of acoustic signals received on a coherent hydrophone array with multiple-nested uniformly-spaced subapertures, such as the ONR-FORA, by nonuniform array beamforming. Finally, we develop a low-cost non-oil-filled towable prototype hydrophone array that consists of eight hydrophone elements with real-time data acquisition and 100 m tow cable. The approach demonstrated here will be applied in the development of a full 160 element POAWRS-type low-cost coherent hydrophone array system in the future.
- Professor Purnima Ratilal-Makris (Advisor)
- Professor Yongmin Liu
- Dr. J. Michael Jech
- Dr. Nils Olav Handegard