Dettmer Jan, Dosso Stan E, Holland Charles W
School of Earth and Ocean Sciences, University of Victoria, Victoria, BC, Canada.
J Acoust Soc Am. 2009 Feb;125(2):706-16. doi: 10.1121/1.3056553.
This paper applies Bayesian inference, including model selection and posterior parameter inference, to inversion of seabed reflection data to resolve sediment structure at a spatial scale below the pulse length of the acoustic source. A practical approach to model selection is used, employing the Bayesian information criterion to decide on the number of sediment layers needed to sufficiently fit the data while satisfying parsimony to avoid overparametrization. Posterior parameter inference is carried out using an efficient Metropolis-Hastings algorithm for high-dimensional models, and results are presented as marginal-probability depth distributions for sound velocity, density, and attenuation. The approach is applied to plane-wave reflection-coefficient inversion of single-bounce data collected on the Malta Plateau, Mediterranean Sea, which indicate complex fine structure close to the water-sediment interface. This fine structure is resolved in the geoacoustic inversion results in terms of four layers within the upper meter of sediments. The inversion results are in good agreement with parameter estimates from a gravity core taken at the experiment site.
本文将贝叶斯推理，包括模型选择和后验参数推断，应用于海底反射数据反演，以解析声源脉冲长度以下空间尺度的沉积物结构。采用了一种实用的模型选择方法，利用贝叶斯信息准则来确定充分拟合数据所需的沉积物层数，同时满足简约性以避免过度参数化。使用高效的Metropolis-Hastings算法对高维模型进行后验参数推断，并将结果表示为声速、密度和衰减的边际概率深度分布。该方法应用于地中海马耳他高原收集的单反射数据的平面波反射系数反演，结果表明靠近水-沉积物界面存在复杂的精细结构。在地声反演结果中，这种精细结构在沉积物上层一米范围内解析为四层。反演结果与在实验地点采集的重力岩芯的参数估计结果高度一致。
