Measuring and modelling ambient noise in three-dimensional ocean environments

三维海洋环境中的环境噪声测量和建模

• 批准号: RGPIN-2016-04887
• 负责人: Barclay, David
• 金额: $ 2.48万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=709516
• 关键词: Measuring; modelling; ambient; noise; three

Underwater signal processing and signal detection schemes require well-characterized spatial and temporal ambient noise field properties to operate effectively in tasks such as detecting ships, submarines, marine mammals, and other underwater sound sources. Additionally, a detailed understanding of the noise field in the ocean has led to the development of passive methods for querying the physical properties of the ocean, seabed and sub-bottom as well as investigating the physics and statistics of noise source mechanisms such as air-sea interaction, surface wave breaking, rainfall, geophysical processes, and bedload sediment transport. More recently, underwater noise has been proposed as a monitoring tool to study the ecological health of the oceans. The objective of this research program is to develop, validate, and apply new analytic and computational models that accurately predict ambient ocean noise spectral, temporal and spatial properties in arbitrary, realistic, and complex 3D domains. This will be achieved by using a parabolic equation (PE) propagation model, while model validation will be achieved by comparison with field measurements of the depth-dependence of ambient noise made on passive acoustic profilers. This combination of methods will be used to study the effect of inhomogeneities (internal waves, fronts), ocean dynamics and non-uniform surface noise processes (rain storms, ice fields) on the noise field, to develop inversion techniques for estimating sea-ice thickness and geophysical properties of the seabed, and to better detect and localize marine mammals, track ecosystem health, and quantify the role of anthropogenic noise on the marine soundscape. The ability to estimate the relative contributions of anthropogenic, environmental, and biological sound to the overall noise field has applications in acoustical oceanography, such as the estimation of precipitation and wind speeds in shallow water environments and in the presence of persistent shipping and biological noise. A portable computational model has the potential to be an operational tool for underwater security and defence, as well as research in the localization and tracking of marine mammals. The research may be applied in performing acoustic measurements of environmental parameters in remote regions of the ocean, particularly the Arctic, where weather buoys are too easily destroyed by sea ice and storms. An instrument development and field program will support this modelling research. The main objective will be to measure the spatial properties and power spectral density of noise and their relationship to oceanographic and atmospheric conditions, bathymetry and seabed properties, and the physical processes that act as sources. A full-ocean depth vertical profiler will be developed and used to investigate the depth-dependence of power spectral density, and vertical and horizontal coherence.

水下信号处理和信号检测方案需要特征良好的空间和时间环境噪声场特性，以在检测船舶，潜艇，海洋哺乳动物和其他水下声音源等任务中有效运行。此外，对海洋噪声场的详细理解导致了被动方法的开发，以查询海洋，海床和底部的物理特性，并研究了噪声源机制的物理和统计数据，例如空气 - 空气互动，表面波浪破裂，降雨，地球物理过程以及床载沉积物的运输。最近，已经提出了水下噪声作为研究海洋生态健康的监测工具。 该研究计划的目的是开发，验证和应用新的分析和计算模型，这些模型在任意，现实和复杂的3D域中准确预测环境噪声光谱，时间和空间特性。这将通过使用抛物线方程（PE）传播模型来实现，而模型验证将通过与被动声学概况剂的环境噪声的深度依赖性进行比较来实现。这种方法的组合将用于研究不均匀性（内部波，前部），海洋动力学和非均匀的表面噪声过程（暴雨，冰场，冰场）对噪声场的影响，以开发反转技术，以估算海冰厚度和量化海洋杂物的噪声，并在海上潮汐的噪声和量化的噪声，并在海上的噪声中估算海上的角色，并在海上妈妈的噪声中进行量化，并将其定量。海洋音景。 估计人为，环境和生物学声音对整个噪声场的相对贡献的能力在声学海洋学中应用，例如在浅水环境中估算降水和风速，以及存在持续的运输和生物噪声。便携式计算模型有可能成为水下安全和防御的操作工具，以及在海洋哺乳动物的定位和跟踪方面的研究。这项研究可用于对海洋偏远地区（尤其是北极地区）的环境参数进行声学测量，那里的气象浮标太容易被海冰和暴风雨摧毁。 仪器开发和现场计划将支持这项建模研究。主要目的是测量噪声的空间特性和功率光谱密度及其与海洋和大气条件，测深和海床特性以及充当来源的物理过程的关系。将开发并使用全海深垂直分析器，以研究功率谱密度的深度依赖性，以及垂直和水平的连贯性。