长期声学数据集中水下地震气枪信号的早期和晚期声学测量
Early and Late Time Acoustic Measures for Underwater Seismic Airgun Signals In Long-Term Acoustic Data Sets
摘要：
这项工作提出了一个新的工具包，用于描述海洋环境的声学特性之前，期间和之后的声音事件所造成的水下地震气枪。该工具包使用现有的声音测量，但独特地将这些应用于捕获早期时间段（实际脉冲）和晚期时间段（混响和多次到达）。总共为每个气枪声音产生183个特征。在格陵兰巴芬湾进行为期46天的地震气枪调查期间，对从实地部署的五个海洋自主记录装置中检索的数据使用了这一工具包。使用这一工具包，从格陵兰部署记录中确定了总共1.47亿个数据点。提取大量的功能，然后使用两种不同的方法进行评估的可行性：串行计算机和高性能系统。结果表明，串行系统的数据提取性能估计需要216小时，高性能计算机需要18小时。本文提供了一个新的工具包的分析说明，以及使用它来确定相关数据的细节。
英文摘要：
This work presents a new toolkit for describing the acoustic properties of the ocean environment before, during and after a sound event caused by an underwater seismic air-gun. The toolkit uses existing sound measures, but uniquely applies these to capture the early time period (actual pulse) and late time period (reverberation and multiple arrivals). In total, 183 features are produced for each air-gun sound. This toolkit was utilized on data retrieved from a field deployment encompassing five marine autonomous recording units during a 46-day seismic air-gun survey in Baffin Bay, Greenland. Using this toolkit, a total of 147 million data points were identified from the Greenland deployment recordings. The feasibility of extracting a large number of features was then evaluated using two separate methods: a serial computer and a high performance system. Results indicate that data extraction performance took an estimated 216 hours for the serial system, and 18 hours for the high performance computer. This paper provides an analytical description of the new toolkit along with details for using it to identify relevant data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
