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DTSTART;TZID=America/New_York:20201210T090000
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UID:4618-1607590800-1607594400@ece.northeastern.edu
SUMMARY:ECE PhD Dissertation Defense: Chenyang Zhu
DESCRIPTION:PhD Dissertation Defense: Remote Monitoring of Multiple Ships over Instantaneous Continental-shelf Scale Region with a Large-aperture Coherent Hydrophone Array \nChenyang Zhu \nLocation: Zoom Link \nAbstract: Multiple mechanized ocean vessels\, including both surface ships and submerged vehicles\, can be simultaneously monitored over instantaneous continental-shelf scale regions >10\,000 km 2 via passive ocean acoustic waveguide remote sensing. A large-aperture densely-sampled coherent hydrophone array system is employed in the Norwegian Sea in Spring 2014 to provide directional sensing in 360 degree horizontal azimuth and to significantly enhance the signal-to-noise ratio (SNR) of ship-radiated underwater sound\, which improves ship detection ranges by roughly two orders of magnitude over that of a single hydrophone. Here\, 30 mechanized ocean vessels spanning ranges from nearby to over 150 km from the coherent hydrophone array\, are detected\, localized and classified. The vessels are comprised of 20 identified commercial ships and 10 unidentified vehicles present in 8 h/day of POAWRS observation for two days. The underwater sounds from each of these ocean vessels received by the coherent hydrophone array are dominated by narrowband signals that are either constant frequency tonals or have frequencies that waver or oscillate slightly in time. The estimated bearing-time trajectory of a sequence of detections obtained from coherent beamforming are employed to determine the horizontal location of each vessel using the Moving Array Triangulation (MAT) technique. For commercial ships present in the region\, the estimated horizontal positions obtained from passive acoustic sensing are verified by Global Positioning System (GPS) measurements of the ship locations found in historical AIS database. We provide time-frequency characterizations of the underwater sounds radiated from the commercial ships and the unidentified vessels. The time-frequency features along with the bearing-time trajectory of the detected signals are applied to simultaneously track and distinguish these vessels.\nNext\, three approaches for simultaneous ship long-range automatic detection\, acoustic signature characterization\, and bearing-time trajectory estimation have been developed and applied\, each focusing on a different aspect of a ship’s radiated underwater sound received on a large-aperture densely-sampled coherent hydrophone array. (i) Ships narrowband machinery tonal sound is analyzed via temporal coherence using Mean Magnitude-Squared Coherence (MMSC) calculations. (ii) Ships broadband cavitation noise amplitude modulated by propeller rotation 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 averaged across specific broad bandwidths are calculated to detect and compare output sound pressure levels from acoustically energetic ships. Each of these techniques are applied after coherent beamforming of the received acoustic signals on a coherent hydrophone array\, leading to significantly enhanced signal-to-noise ratios for simultaneous detection and characterization of multiple ships over continental-shelf scale regions. The approaches are illustrated by application to\nroughly two hours of acoustic recordings of a 160-element coherent hydrophone array deployed in the Norwegian Sea during an experiment in February 2014. Six ocean vessels are simultaneously detected and their acoustic signatures characterized\, located at a variety of bearings and ranges out to 200 km from the coherent hydrophone array\, with speeds ranging from 0.5 knots to 13 knots\, verified by Global Positioning System (GPS) information from Automatic Identification System (AIS) database. Hybrid usage of the three methods provide a robust approach for ship characterization in terms of machinery tonal sound signature\, propeller rotation signature\, and ship broadband energetics that can be employed for efficient ship classification. The CSC approach is demonstrated to be also useful for automatic detection and bearing-time estimation of repetitive marine mammal vocalizations present in coherent hydrophone array recordings\, providing estimates of inter-pulse-train and inter-pulse intervals from CSC spectra cyclic fundamental and first recurring peak frequencies respectively.
URL:https://ece.northeastern.edu/event/ece-phd-dissertation-defense-chenyang-zhu/
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