Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543, USA.
Duke University Marine Laboratory, Beaufort, North Carolina 28516, USA.
J Acoust Soc Am. 2023 Feb;153(2):1094. doi: 10.1121/10.0017118.
The low-frequency impulsive gunshot vocalizations of baleen whales exhibit dispersive propagation in shallow-water channels which is well-modeled by normal mode theory. Typically, underwater acoustic source range estimation requires multiple time-synchronized hydrophone arrays which can be difficult and expensive to achieve. However, single-hydrophone modal dispersion has been used to range baleen whale vocalizations and estimate shallow-water geoacoustic properties. Although convenient when compared to sensor arrays, these algorithms require preliminary signal detection and human labor to estimate the modal dispersion. In this paper, we apply a temporal convolutional network (TCN) to spectrograms from single-hydrophone acoustic data for simultaneous gunshot detection and ranging. The TCN learns ranging and detection jointly using gunshots simulated across multiple environments and ranges along with experimental noise. The synthetic data are informed by only the water column depth, sound speed, and density of the experimental environment, while other parameters span empirically observed bounds. The method is experimentally verified on North Pacific right whale gunshot data collected in the Bering Sea. To do so, 50 dispersive gunshots were manually ranged using the state-of-the-art time-warping inversion method. The TCN detected these gunshots among 50 noise-only examples with high precision and estimated ranges which closely matched those of the physics-based approach.
须鲸的低频脉冲枪声在浅水中的声道中表现出弥散传播，这很好地符合模态理论。通常，水下声源远估计需要多个时间同步的水听器阵列，这在实现上可能很困难且昂贵。然而，单水听器模态色散已被用于对须鲸叫声进行测距，并估计浅海的地球物理性质。虽然与传感器阵列相比更为方便，但这些算法需要进行初步的信号检测和人工劳动来估计模态色散。在本文中，我们应用了一个时间卷积网络（TCN）来对单水听器声数据的声谱图进行枪击检测和测距。TCN 使用在多个环境和范围内模拟的枪击声以及实验噪声来联合学习测距和检测。合成数据仅由实验环境的水柱深度、声速和密度来提供信息，而其他参数则跨越经验观察到的范围。该方法在白令海采集的北太平洋露脊鲸枪击数据上进行了实验验证。为此，我们使用最先进的时频扭曲反演方法对 50 个分散的枪击声进行了手动测距。TCN 在 50 个仅有噪声的示例中以高精度检测到了这些枪击声，并估计的范围与基于物理的方法非常接近。
