Thode Aaron M, Conrad Alexander S, Ozanich Emma, King Rylan, Freeman Simon E, Freeman Lauren A, Zgliczynski Brian, Gerstoft Peter, Kim Katherine H
Scripps Institution of Oceanography, University of California San Diego, La Jolla, California 92093-0238, USA.
Greeneridge Sciences, Inc., 90 Arnold Place, Suite D, Santa Barbara, California 93117, USA.
J Acoust Soc Am. 2021 Feb;149(2):770. doi: 10.1121/10.0003382.
Detecting acoustic transients by signal-to-noise ratio (SNR) becomes problematic in nonstationary ambient noise environments characteristic of coral reefs. An alternate approach presented here uses signal directionality to automatically detect and localize transient impulsive sounds collected on underwater vector sensors spaced tens of meters apart. The procedure, which does not require precise time synchronization, first constructs time-frequency representations of both the squared acoustic pressure (spectrogram) and dominant directionality of the active intensity (azigram) on each sensor. Within each azigram, sets of time-frequency cells associated with transient energy arriving from a consistent azimuthal sector are identified. Binary image processing techniques then link sets that share similar duration and bandwidth between different sensors, after which the algorithm triangulates the source location. Unlike most passive acoustic detectors, the threshold criterion for this algorithm is bandwidth instead of pressure magnitude. Data collected from shallow coral reef environments demonstrate the algorithm's ability to detect SCUBA bubble plumes and consistent spatial distributions of somniferous fish activity. Analytical estimates and direct evaluations both yield false transient localization rates from 3% to 6% in a coral reef environment. The SNR distribution of localized pulses off Hawaii has a median of 7.7 dB and interquartile range of 7.1 dB.
在具有珊瑚礁特征的非平稳环境噪声中，通过信噪比（SNR）检测声学瞬变信号存在问题。本文提出的另一种方法利用信号方向性来自动检测和定位在相距数十米的水下矢量传感器上收集到的瞬态脉冲声。该过程不需要精确的时间同步，首先构建每个传感器上声压平方（频谱图）和有效强度主导方向性（方位图）的时频表示。在每个方位图内，识别与来自一致方位扇区的瞬态能量相关的时频单元集。然后，二元图像处理技术将不同传感器之间具有相似持续时间和带宽的集连接起来，之后算法对源位置进行三角测量。与大多数被动声学探测器不同，该算法的阈值标准是带宽而不是压力幅度。从浅珊瑚礁环境收集的数据证明了该算法检测水肺潜水气泡羽流以及嗜睡鱼类活动一致空间分布的能力。在珊瑚礁环境中，分析估计和直接评估得出的虚假瞬态定位率均为3%至6%。夏威夷附近局部脉冲的SNR分布中位数为7.7dB，四分位间距为7.1dB。
