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arXiv 2402.07930physics.flu-dynmath.OCphysics.ao-ph

从海底噪声压力测量中实现水波的最优重构

Optimal reconstruction of water-waves from noisy pressure measurements at the seabed

Joris Labarbe, Alexandre Vieira, Didier Clamond

AI总结:

针对从含噪海底压力测量中恢复表面波剖面的问题,提出一种基于最小化恢复压力与测量值距离的优化方法,有效克服了直接法对噪声敏感的缺陷,成功实现了从含噪数据中恢复重力-毛细波。

摘要:

我们考虑在表面压力(先验未知)任意的情况下,从含噪海底压力测量中恢复表面波剖面的问题。在没有噪声时,clamond2023steady 中开发的直接方法提供了一种有效的恢复海表面的途径。然而,测量的解析性假设使得该方法在存在噪声时效率低下。因此,我们引入了一种基于最小化恢复的海底压力与其测量值之间距离的优化程序。该方法被证明非常适合处理受扰动的信号。我们展示了该方法从未经滤波的含噪数据中恢复重力-毛细波的有效性。

英文摘要:

We consider the problem of recovering the surface wave profile from noisy bottom pressure measurements with (\textit{a priori} unknown) arbitrary pressure at the surface. Without noise, the direct approach developed in \cite{clamond2023steady} provides an effective way to recover the sea surface. However, the assumption of analyticity for the measurement renders this method inefficient in the presence of noise. Therefore, we introduce an optimisation procedure based on the minimisation of a distance between a recovered bottom pressure and its measurement. Such method proves to be well-designed to handle perturbed signals. We illustrate the effectiveness of this approach in the recovery of gravity-capillary waves from unfiltered noisy data.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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