Thomas Rebecca E, Fristrup Kurt M, Tyack Peter L
Biology Department, Woods Hole Oceanographic Institution, Massachusetts 02543, USA.
J Acoust Soc Am. 2002 Oct;112(4):1692-701. doi: 10.1121/1.1494805.
It is difficult to attribute underwater animal sounds to the individuals producing them. This paper presents a system developed to solve this problem for dolphins by linking acoustic locations of the sounds of captive bottlenose dolphins with an overhead video image. A time-delay beamforming algorithm localized dolphin sounds obtained from an array of hydrophones dispersed around a lagoon. The localized positions of vocalizing dolphins were projected onto video images. The performance of the system was measured for artificial calibration signals as well as for dolphin sounds. The performance of the system for calibration signals was analyzed in terms of acoustic localization error, video projection error, and combined acoustic localization and video error. The 95% confidence bounds for these were 1.5, 2.1, and 2.1 m, respectively. Performance of the system was analyzed for three types of dolphin sounds: echolocation clicks, whistles, and burst-pulsed sounds. The mean errors for these were 0.8, 1.3, and 1.3 m, respectively. The 95% confidence bound for all vocalizations was 2.8 m, roughly the length of an adult bottlenose dolphin. This system represents a significant advance for studying the function of vocalizations of marine animals in relation to their context, as the sounds can be identified to the vocalizing dolphin and linked to its concurrent behavior.
很难将水下动物发出的声音与发出这些声音的个体联系起来。本文介绍了一种开发的系统，通过将圈养宽吻海豚声音的声学位置与头顶上方的视频图像相链接，来解决海豚的这一问题。一种时延波束形成算法对从分散在泻湖周围的水听器阵列获取的海豚声音进行定位。发出声音的海豚的定位位置被投影到视频图像上。该系统针对人工校准信号以及海豚声音进行了性能测量。从声学定位误差、视频投影误差以及声学定位与视频综合误差方面分析了该系统在校准信号方面的性能。这些误差的95%置信区间分别为1.5米、2.1米和2.1米。针对三种类型的海豚声音分析了该系统的性能：回声定位咔哒声、哨声和猝发脉冲声。这些声音的平均误差分别为0.8米、1.3米和1.3米。所有发声的95%置信区间为2.8米，大致是一只成年宽吻海豚的长度。该系统代表了在研究海洋动物发声功能与其所处环境关系方面的一项重大进展，因为声音可以被识别为发声海豚发出的，并与其同时发生的行为相联系。
