Sagers Jason D, Knobles David P
Applied Research Laboratories, The University of Texas at Austin, P.O. Box 8029, Austin, Texas 78713-8029.
J Acoust Soc Am. 2014 Jun;135(6):3327-37. doi: 10.1121/1.4873515.
Addressed is the statistical inference of the sound-speed depth profile of a thick soft seabed from broadband sound propagation data recorded in the Gulf of Oman Basin in 1977. The acoustic data are in the form of time series signals recorded on a sparse vertical line array and generated by explosive sources deployed along a 280 km track. The acoustic data offer a unique opportunity to study a deep-water bottom-limited thickly sedimented environment because of the large number of time series measurements, very low seabed attenuation, and auxiliary measurements. A maximum entropy method is employed to obtain a conditional posterior probability distribution (PPD) for the sound-speed ratio and the near-surface sound-speed gradient. The multiple data samples allow for a determination of the average error constraint value required to uniquely specify the PPD for each data sample. Two complicating features of the statistical inference study are addressed: (1) the need to develop an error function that can both utilize the measured multipath arrival structure and mitigate the effects of data errors and (2) the effect of small bathymetric slopes on the structure of the bottom interacting arrivals.
本文探讨了根据1977年在阿曼湾盆地记录的宽带声传播数据推断厚软海底声速深度剖面的统计推断问题。声学数据以时间序列信号的形式记录在稀疏垂直线阵列上，由沿280公里轨迹部署的爆炸源产生。由于大量的时间序列测量、极低的海底衰减和辅助测量，声学数据为研究深水底部受限的厚沉积环境提供了独特的机会。采用最大熵方法获得声速比和近表面声速梯度的条件后验概率分布（PPD）。多个数据样本允许确定唯一指定每个数据样本的PPD所需的平均误差约束值。讨论了统计推断研究的两个复杂特征：（1）需要开发一种既能利用测量的多径到达结构又能减轻数据误差影响的误差函数；（2）小测深坡度对底部相互作用到达结构的影响。
