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利用来自异步记录仪的到达时间差数据对弓头鲸进行定位。

Bowhead whale localization using time-difference-of-arrival data from asynchronous recorders.

作者信息

Warner Graham A, Dosso Stan E, Hannay David E

机构信息

School of Earth and Ocean Sciences, University of Victoria, 3800 Finnerty Road, Suite 405A, Victoria, British Columbia V8P 5C2, Canada.

JASCO Applied Sciences, 2305-4464 Markham Street, Victoria, British Columbia V8Z 7X8, Canada.

出版信息

J Acoust Soc Am. 2017 Mar;141(3):1921. doi: 10.1121/1.4978438.

Abstract

This paper estimates bowhead whale locations and uncertainties using nonlinear Bayesian inversion of the time-difference-of-arrival (TDOA) of low-frequency whale calls recorded on onmi-directional asynchronous recorders in the shallow waters of the northeastern Chukchi Sea, Alaska. A Y-shaped cluster of seven autonomous ocean-bottom hydrophones, separated by 0.5-9.2 km, was deployed for several months over which time their clocks drifted out of synchronization. Hundreds of recorded whale calls are manually associated between recorders. The TDOA between hydrophone pairs are calculated from filtered waveform cross correlations and depend on the whale locations, hydrophone locations, relative recorder clock offsets, and effective waveguide sound speed. A nonlinear Bayesian inversion estimates all of these parameters and their uncertainties as well as data error statistics. The problem is highly nonlinear and a linearized inversion did not produce physically realistic results. Whale location uncertainties from nonlinear inversion can be low enough to allow accurate tracking of migrating whales that vocalize repeatedly over several minutes. Estimates of clock drift rates are obtained from inversions of TDOA data over two weeks and agree with corresponding estimates obtained from long-time averaged ambient noise cross correlations. The inversion is suitable for application to large data sets of manually or automatically detected whale calls.

摘要

本文利用阿拉斯加楚科奇海东北部浅水区全向异步记录仪记录的低频鲸鱼叫声的到达时间差(TDOA)进行非线性贝叶斯反演,估算了弓头鲸的位置及其不确定性。部署了由七个自主海底水听器组成的Y形阵列,间距为0.5 - 9.2千米,持续数月,在此期间它们的时钟逐渐不同步。数百个记录的鲸鱼叫声在记录仪之间进行人工关联。水听器对之间的TDOA通过滤波后的波形互相关计算得出,它取决于鲸鱼位置、水听器位置、记录仪相对时钟偏移以及有效波导声速。非线性贝叶斯反演可估算所有这些参数及其不确定性以及数据误差统计量。该问题高度非线性,线性化反演未产生符合物理实际的结果。非线性反演得到的鲸鱼位置不确定性可低至足以精确跟踪在几分钟内反复发声的迁徙鲸鱼。通过对两周内的TDOA数据进行反演获得时钟漂移率估计值,且与从长时间平均环境噪声互相关得到的相应估计值一致。该反演适用于应用于手动或自动检测到的鲸鱼叫声的大型数据集。

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