An Inversion Method for Geoacoustic Parameters in Shallow Water Based on Bottom Reflection Signals

反演(地质) 地质学 海床 波浪和浅水 声学 海底扩张 反变换采样 反射(计算机编程) 水下 地震学 光学 地球物理学 海洋学 计算机科学 表面波 物理 构造学 程序设计语言
作者
Zhuo Wang,Yuxuan Ma,Guangming Kan,Baohua Liu,Xinghua Zhou,Xiaobo Zhang
出处
期刊:Remote Sensing [Multidisciplinary Digital Publishing Institute]
卷期号:15 (13): 3237-3237 被引量:3
标识
DOI:10.3390/rs15133237
摘要

The inversion method based on the reflection loss-grazing angle curve is an effective tool to obtain local underwater acoustic parameters. Because geoacoustic parameters vary in sensitivity to grazing angle, it is difficult to get accurate results in geoacoustic parameter inversion based on small-grazing-angle data in shallow water. In addition, the normal-mode model commonly used in geoacoustic parameter inversion fails to meet the needs of accurate local sound field simulation as the influence of the secant integral is ignored. To solve these problems, an acoustic data acquisition scheme was rationally designed based on a sparker source, a fixed vertical array, and ship drifting with the swell, which could balance the trade-off among signal transmission efficiency and signal stability, and the actual local acoustic data at low-to-mid frequencies were acquired at wide grazing angles in the South Yellow Sea area. Furthermore, the bottom reflection coefficients (bottom reflection losses) corresponding to different grazing angles were calculated based on the wavenumber integration method. The local seafloor sediment parameters were then estimated using the genetic algorithm and the bottom reflection loss curve with wide grazing angles, obtaining more accurate local acoustic information. The seafloor acoustic velocity inverted is cp=1659 m/s and the sound attenuation is αp=0.656 dB/λ in the South Yellow Sea. Relevant experimental results indicate that the method described in this study is feasible for local inversion of geoacoustic parameters for seafloor sediments. Compared with conventional large-scale inversion methods, in areas where there are significant changes in the seabed sediment level, this method can obtain more accurate local acoustic features within small-scale areas.
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