Quantitative processing of broadband data as implemented in a scientific split-beam echosounder

Lars Nonboe Andersen,Dezhang Chu, Nils Olav Handegard,Harald Heimvoll,Rolf Korneliussen,Gavin J. Macaulay,Egil Ona, Ruben Patel,Geir Pedersen

METHODS IN ECOLOGY AND EVOLUTION(2024)

引用 0|浏览5
暂无评分
摘要
The use of quantitative broadband echosounders for biological studies and surveys can offer considerable advantages over narrowband echosounders. These include improved spectral-based target identification and significantly increased ability to resolve individual targets. An understanding of current processing steps is required to fully utilise and further develop broadband acoustic methods in marine ecology.We describe the steps involved in processing broadband acoustic data from raw data to frequency dependent target strength (TSf$$ \mathrm{TS}(f) $$) and volume backscattering strength (Svf$$ {S}_{\mathrm{v}}(f) $$) using data from the EK80 broadband scientific echosounder as examples. Although the overall processing steps are described and build on established methods from the literature, multiple choices need to be made during implementation.To highlight and discuss some of these choices and facilitate a common understanding within the community, we have also developed a Python code which will be made publicly available and open source. The code follows the steps using raw data from two single pings, showing the step-by-step processing from raw data to TSf$$ \mathrm{TS}(f) $$ and Svf$$ {S}_{\mathrm{v}}(f) $$.This code can serve as a reference for developing custom code or implementation in existing processing pipelines, as an educational tool and as a starting point for further development of broadband acoustic methods in fisheries acoustics.
更多
查看译文
关键词
broadband acoustic backscattering,community ecology,conservation,habitats,matched-filter signal processing,monitoring (community ecology),monitoring (population ecology),population ecology,scientific echosounders
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要