发表机构
Institut de Ciències del Mar (ICM-CSIC); Institut de Física Corpuscular (IFIC), Centre Mixte Universitat de València (UV-CSIC)（海洋科学研究所（ICM-CSIC）; 粒子物理研究所（IFIC），瓦伦西亚大学-西班牙高等科研理事会混合中心（UV-CSIC））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出基于分布式光纤声波传感（DAS）的端到端工作流程，实现长须鲸歌声的检测、特征表征与定位，经实测精度与召回率表现良好，为长须鲸监测提供了集成框架。
AI 中文摘要
配备分布式光纤声波传感（DAS）的海底光缆为长须鲸的大规模监测提供了有效方法。我们提出一种用于长须鲸音符检测、表征与定位的端到端工作流程，在直布罗陀海峡和西阿尔沃兰海的两条海底电信光缆上进行了测试。该工作流程采用适配窄带长须鲸音符的峰度值拾取器，通过基于密度的时空聚类、聚类合并及双曲线拟合将通道级检测结果分组为单个音符，以剔除不连贯的拾取结果。保留的聚类通过时间、频谱和能量相关描述符进行表征，支持音符类型判别和音符间间隔估计。随后利用DAS通道间的相对到达时间，通过网格搜索程序估计候选声源位置。对6段长须鲸歌声的人工标注检测结果进行评估，得到拾取级的中位数精度为0.990、召回率为0.744，聚类级的中位数精度为0.880、召回率为0.806。代表性应用展示了重叠发声的分离、A型与B型音符的表征以及表观声源运动的推断。通过将密集的DAS记录转换为紧凑的音符级生物声学信息，该工作流程为长须鲸监测提供了集成框架，并为适配其他同步声学接收器阵列奠定了基础。
英文摘要
Submarine fiber-optic cables instrumented with distributed acoustic sensing (DAS) provide an effective approach for large-scale monitoring of fin whales. We present an end-to-end workflow for detecting, characterizing, and localizing fin whale notes, tested on two submarine telecom cables in the Strait of Gibraltar and western Alboran Sea. The workflow applies a kurtosis-value picker adapted to narrow-band fin whale notes. Channel-wise detections are grouped into individual notes using density-based spatio-temporal clustering, cluster agglomeration, and hyperbolic fitting to reject incoherent picks. The retained clusters are characterized through temporal, spectral, and energy-related descriptors that support note-type discrimination and estimation of inter-note intervals. Relative arrival times across DAS channels are then used in a grid-search procedure to estimate candidate source locations. Evaluation against manually annotated detections from six fin whale songs yielded median pick-level precision of 0.990 and recall of 0.744, and median cluster-level precision of 0.880 and recall of 0.806. Representative applications demonstrate separation of overlapping vocalizations, characterization of type-A and type-B notes, and the inference of apparent source movement. By transforming dense DAS recordings into compact note-level bioacoustic information, the workflow provides an integrated framework for fin whale monitoring and a basis for adaptation to other synchronized acoustic receiver arrays.
Comments14 pages, 8 figures, 2 tables. Manuscript in preparation for journal submission
