Development of split-beam sonar processing methods

分束声纳处理方法的发展

• 批准号: 560255-2020
• 负责人: Zedel, LeonardLJ
• 金额: $ 1.67万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=763207
• 关键词: Development; split; beam; sonar; processing

Acoustic methods used to evaluate fish size and distribution are an important component of fisheries management and oceanographic research studies. Except for some specialised applications, acoustic methods use echosounder systems that are deployed from ships to sample a survey pattern in some area of the ocean. Deployment from ships has been required because acoustic survey instrumentation consumes a lot of power and collects large quantities of data. However, over the last 10 years, ASL Environmental Sciences Inc. (ASL) has developed low power acoustic instrumentation with large recording capacity suitable for use in a self-contained package. This capability opens up two new revolutionary survey possibilities: long-term monitoring from fixed locations that are far from shore or are not easily accessible (for example under ice) and; the ability to undertake surveys using small autonomous vehicles. The proposed project will capitalise on that capability to enable fish detection in their acoustic systems by incorporating "split-beam" sonar processing. With split-beam sonar, the acoustic beam used to probe the water is divided into four quadrants which makes it possible to identify the angular position of a target in addition to its range. That additional information makes it possible to make measurements of fish size and to track fish behaviour. The project involves the development of new acoustic hardware and signal processing software suitable for operating in a self-contained autonomous package. In addition to the hardware developments, computer simulations of sonar operation will be used to explore optimal methods for signal processing. A series of field trials will be used to fine tune and demonstrate the capabilities of the approach. This research will optimize a revolutionary survey product for ASL and improve methods for extracting and understanding information contained in sonar data - advancements with potential economic and environmental benefits to Canada.

用于评估鱼类大小和分布的声学方法是渔业管理和海洋学研究的重要组成部分。 除了一些专门的应用，声学方法使用回声测深仪系统，部署在船上，在海洋的某些区域进行调查模式的采样。由于声学勘测仪器消耗大量电力并收集大量数据，因此需要从船上部署。然而，在过去的10年里，ASL环境科学公司。(ASL)已经开发出适合于在独立封装中使用的具有大记录容量的低功率声学仪器。 这种能力开辟了两种新的革命性调查可能性：从远离海岸或不易接近的固定位置（例如冰下）进行长期监测;以及使用小型自动驾驶车辆进行调查的能力。 拟议的项目将利用这种能力，通过结合“分束”声纳处理，使鱼类在其声学系统中进行探测。使用分束声纳，用于探测水的声束被分成四个象限，这使得除了目标的范围之外，还可以识别目标的角位置。这些额外的信息使测量鱼的大小和跟踪鱼的行为成为可能。该项目涉及开发新的声学硬件和信号处理软件，适用于在一个独立的自主包中运行。 除了硬件的发展，声纳操作的计算机模拟将用于探索信号处理的最佳方法。 一系列的现场试验将被用来微调和证明的能力的方法。 这项研究将优化ASL的革命性调查产品，并改进提取和理解声纳数据中包含的信息的方法-这些进步对加拿大具有潜在的经济和环境效益。