使用深度学习,光谱图交叉相关性和非线性贝叶斯反转来检测和定位北大西洋真
Romina A S Gehrmann1, Oliver S Kirsebom2, Bruno Padovese3
1Defence Research and Development Canada, Dartmouth, Nova Scotia, Canada.
The Journal of the Acoustical Society of America
|March 11, 2026
概括
我们开发了一种新的方法来检测和定位北大西洋真 (NARW) 呼叫,使用水下声音. 这种被动声学监控技术有助于保护这个危物种免受人类威胁.
科学领域:
- 海洋生物学 海洋生物学
- 声学 声学 在声学方面
- 保护技术 保护技术
背景情况:
- 北大西洋正 (NARW) 处于极度危状态,面临船只撞击和渔具的威胁.
- 被动声学监测 (PAM) 对于跟踪海洋哺乳动物和实施保护战略至关重要.
- 有效地检测和定位NARW声调对于减轻人类造成的风险至关重要.
研究的目的:
- 为检测和定位北大西洋真 (NARW) 呼叫提供一个强大的处理程序.
- 为了证明三步被动声学监测分析作为NARW保护缓解工具的有效性.
- 增强声学调查所提供的信息,以有效管理.
主要方法:
- 利用一个sonobuoy网格被动记录NARW电话 (呼叫和吟) 在圣劳伦斯湾南部.
- 采用深度学习模型用于初始NARW呼叫检测,适用于sonobuoy数据集.
- 应用光谱图相关性用于电话关联和到达时间差 (TDOA) 估计在sonobuoys.
- 执行非线性贝叶斯反转用于呼叫本地化,包括不确定性估计.
主要成果:
- 通过使用开发的三步分析,成功检测并定位了北大西洋右 (NARW) 的呼叫.
- 这种方法在sonobuoy电网内和附近的电话中被证明有效.
- 分析提供了对通话源头头寸的现实不确定性估计.
- 与传统的视觉调查相比,声学数据增强了信息.
结论:
- 提出的处理程序是检测和定位北大西洋真 (NARW) 发声的有效工具.
- 这种被动声学监测方法显著支持危鱼的保护和管理工作.
- 该方法提供了改进的空间和时间信息,以减轻人类对NARW人口的影响.
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