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Lookup NU author(s): Dr Gavin LowesORCiD,
Professor Jeffrey Neasham,
Dr Charalampos TsimenidisORCiD
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This paper presents work towards developing a low-power, low-cost underwater passive acoustic monitoring network. The main aim is to accurately detect passing vessels by exploiting the acoustic signature emitted during propeller cavitation. To achieve this a novel combination of analogue signal processing and embedded programming has been created. The vessel detection system has been integrated with a very low power piece of hardware, developed by Newcastle University, capable of underwater acoustic communication. The vessel detector is based on the principles of the Detection of Envelope Modulation on Noise (DEMON) algorithm . Using this method, along with statistical standard error of the estimate analysis, decisions are made as to whether or not a vessel is present. These decisions are then transmitted acoustically via an underwater wireless network to the end-user. In field trials carried out, the system demonstrated the ability to both detect vessels and communicate results reliably whilst maintaining the low-power, low-cost ethos of this project. Future research is planned to utilise the low-power vessel detection system developed to trigger a higher power mode. This mode will sample the raw audio as opposed to the current method which samples only the signal's envelope. This will allow for a full spectral analysis of the vessel's signature enabling feature extraction and individual vessel characterisation.
Author(s): Lowes GJ, Neasham JA, Burnett R, Tsimenidis CC
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Oceans 2019 MTS/IEEE Seattle
Year of Conference: 2019
Online publication date: 20/01/2020
Acceptance date: 27/10/2019
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