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    Reducing bias due to noise and attenuation in open-ocean echo integration data

    Access Status
    Fulltext not available
    Authors
    Ryan, T.
    Downie, R.
    Kloser, Rudy
    Keith, G.
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Ryan, T. and Downie, R. and Kloser, R. and Keith, G. 2015. Reducing bias due to noise and attenuation in open-ocean echo integration data. ICES Journal of Marine Science. 72 (8): pp. 2482-2493.
    Source Title
    ICES Journal of Marine Science
    DOI
    10.1093/icesjms/fsv121
    ISSN
    1054-3139
    School
    Centre for Marine Science and Technology
    URI
    http://hdl.handle.net/20.500.11937/52879
    Collection
    • Curtin Research Publications
    Abstract

    © 2015 International Council for the Exploration of the Sea All rights reserved.Measurements of mean volume backscattering strength (Sv, dB re 1 m21) at ocean-basin scale were made using 38-kHz hull-mounted echosounders on ships of opportunity as part of Australia's Integrated Marine Observing System. The datawere collected on vessels of various designs, none of which were purposely built for collecting high-quality acoustic data. A full range of weather extremes affected the quality of the data and could cause large biases in Sv. To remove first-order biases and improve processing efficiency, a sequence of new and existing data processing filters were applied in a semi-Automated procedure. These filters were designed to mitigate the effects of three types of noise: impulsive (less than one ping), transient (multiple pings), and background (hours or longer).Afilterwas also applied to identify signals thatwere attenuated by air bubbles beneath the transducer. These filters were applied to data from transits across the Southwest Pacific, Indian, and Southern Oceans to produce qualitycontrolled Sv datasets that are now available from a publicly accessible repository. These filters may be relevant to other open-ocean acoustic observing endeavours, and one or more could be used to mitigate bias in data from a range of acoustic applications.

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