Abstract
AbstractThere is no established approach for dealing with the active acoustic detection of biological targets in highly dynamic aquatic environments where intense physical interference means that standard techniques are unsuitable. This is a particular problem in ecologically important environments with emerging industrial significance such as marine energy extraction sites. We developed an automatic processing method which allows effective target detection with high sensitivity throughout variable acoustic conditions. The method is based on scale‐dependent adaptive filtering of data and morphological analysis of short‐scale backscatter contributions for the exclusion of intense turbulent features and isolation of biological targets. Echosounder platform deployments around marine energy infrastructure in a tidal channel provide test data which demonstrate the effectiveness of the proposed approach. Target validation and assessment is carried out by the analysis of multifrequency characteristics and direct inspection. The results deliver effective, quantitative, and repeatable assessment of ecological interactions and target distributions with clear implications for environmental assessment in high energy sites and promising applications in other contexts.
Highlights
There is no established approach for dealing with the active acoustic detection of biological targets in highly dynamic aquatic environments where intense physical interference means that standard techniques are unsuitable
The main goal of this paper relates to the detection of discrete aggregations of fish capable of independent movement in the strong flows, which we call targets. To achieve this overall goal, we present a flexible methodology capable of target detection over the challenging conditions encountered in marine renewable energy sites
Samples removed by the morphological exclusion in Sv morph are removed from the scale selective filtering results in Sv suppress to give a processed data version (Sv stable), appropriate for standard target detection methodologies. This stabilized data version has mitigated the overwhelming effects of long-scale variations in the background acoustic conditions and short-scale intense turbulent structures so that biological targets are clearly identifiable
Summary
There is no established approach for dealing with the active acoustic detection of biological targets in highly dynamic aquatic environments where intense physical interference means that standard techniques are unsuitable. In highly dynamic and turbulent aquatic environments, the background acoustic characteristics can be extremely variable (Fig. 1) leading to the failure of standard processing approaches for target detection. Processing approaches which seriously limit the depth range or temporal continuity of analysis cannot possibly give a full understanding of the behavior of fish and other targets of interest at highly dynamic sites.
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