基于模态分解和频波数变换的源深度估计

B. Nicolas, J. Mars, J. Lacoume
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引用次数: 6

摘要

浅水环境下声源定位是水声研究的关键问题。许多基于匹配场处理(MFP)或模态分解(也称为模态滤波)的方法已经使用垂直阵列开发出来。传统的模式滤波器使用水听器的垂直阵列来分离模式。在这种情况下,模态振幅通过压力场的空间积分来估计,这在水平阵列中是不可能的。本文提出了一种利用水听器水平阵列记录的压力场进行模态分解来估计震源深度的有效方法。模态振幅估计使用频率-波数变换,这是二维傅里叶变换在时间和径向距离。然后将预测模态振幅与实测模态振幅进行比较,估计震源深度。研究了该方法对噪声的鲁棒性,并给出了在实际数据中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Source depth estimation using modal decomposition and frequency-wavenumber transform
Source localization in shallow water environment is a crucial issue in underwater acoustics. Many methods based on Matched Field Processing (MFP) or on modal decomposition (also called mode filtering) have been developed using a vertical array. The conventional mode filter separates modes using a vertical array of hydrophones. In this case, modes amplitudes are estimated by spatial integration of the pressure field which becomes impossible with a horizontal array. In this paper, we propose an efficient method to estimate the source depth by modal decomposition of the pressure field recorded on a horizontal array of hydrophones. Modes amplitudes are estimated using the frequency-wavenumber transform, which is the 2D Fourier transform in time and radial distance. Then predicted modes amplitudes are compared to measured modes amplitudes, and source depth is estimated. Robustness against noise of the method is studied and application on real data is presented.
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