海洋被动数据的高级自动结构:从点击序列调制到鲸鱼行为分析

F. Caudal, H. Glotin
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引用次数: 3

摘要

本文讨论了利用水听器记录抹香鲸的行为,这要归功于从多发射鲸的实时被动水声跟踪算法中提取的一组特征。声学定位允许研究鲸鱼在深水(几百米)中的行为,而不需要推断环境。在这里,我们使用实时多重跟踪算法,它提供了一个或几个抹香鲸的定位。由于位置坐标和音频文件,我们能够自动标记信号并提取不同的特征,如速度,点击能量,点击间隔(ICI)…这些特征使我们能够交叉分析鲸鱼的行为(觅食、狩猎、摄食),并看到每个参数的影响以及它们之间的依赖关系。最后,我们生成了一个用于描述和有效访问深海鲸类研究声音记录的XML文件,从而导致音频文件的索引和结构。从而便于行为研究在记录中选择和访问相应的索引。完整的方法是在NUWC1和AUTEC2的实际数据上进行处理的。作为示例,我们以单个鲸鱼为例对算法进行处理,并研究了潜水过程中特征与鲸鱼行为的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High level automatic structuration of ocean passive data : From click sequence modulations to whale behavior analyses
This paper discusses on estimating the behavior of a sperm whale using hydrophones recordings thanks to a set of features extracted from a real-time passive underwater acoustic tracking algorithm for multiple emitting whales. Acoustic localization permits to study whales' behavior in deep water (several hundreds of meters) without infering with the environment. Here, we use a real-time multiple tracking algorithm, which provides a localization of one or several sperm whales. Thanks to the positions coordinates and the audio files, we are able to automatically label the signal and to extract different features such as the speed, energy of the clicks, inter-click-interval (ICI)... These features allow us to cross-analyse the whale behavior (foraging , hunting, ingestion) and to see the influence of each parameters and the dependency between them. Finally, we generate a XML file for description and efficient access of deep ocean sound records for cetacean studies, which leads to index and structure the audio files. Thus, the behavior study is facilitated choosing and accessing the corresponding index in the recording. The complete method is processed on real data from the NUWC1 and the AUTEC2. As an illustration, we process the algorithm on a one whale case and study the correlation between the features and the whale behavior during the diving.
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