Kim Daehwan, Kim Donghyeon, Byun Gihoon, Kim Jeasoo, Song Heechun
Department of Ocean Engineering, Korea Maritime and Ocean University, Busan 49112, Republic of Korea.
Scripps Institution of Oceanography, La Jolla, CA 92093-0238, USA.
Sensors (Basel). 2024 Sep 5;24(17):5782. doi: 10.3390/s24175782.
Understanding the characteristics of underwater sound channels is essential for various remote sensing applications. Typically, the time-domain Green's function or channel impulse response (CIR) is obtained using computationally intensive acoustic propagation models that rely on accurate environmental data, such as sound speed profiles and bathymetry. Ray-based blind deconvolution (RBD) offers a less computationally demanding alternative using plane-wave beamforming to estimate the Green's function. However, the presence of noise can obscure low coherence ray arrivals, making accurate estimation challenging. This paper introduces a method using the waveguide invariant to improve the signal-to-noise ratio (SNR) of broadband Green's functions for a moving source without prior knowledge of range. By utilizing RBD and the frequency shifts from the striation slope, we coherently combine individual Green's functions at adjacent ranges, significantly improving the SNR. In this study, we demonstrated the proposed method via simulation and broadband noise data (200-900 Hz) collected from a moving ship in 100 m deep shallow water.
了解水下声道的特性对于各种遥感应用至关重要。通常，时域格林函数或声道脉冲响应（CIR）是使用计算密集型声学传播模型获得的，这些模型依赖于准确的环境数据，如声速剖面和水深测量。基于射线的盲反卷积（RBD）提供了一种计算要求较低的替代方法，使用平面波波束形成来估计格林函数。然而，噪声的存在会掩盖低相干射线的到达，使得准确估计具有挑战性。本文介绍了一种方法，该方法使用波导不变量来提高移动源宽带格林函数的信噪比（SNR），而无需事先知道距离。通过利用RBD和条纹斜率的频率偏移，我们在相邻距离处相干地组合各个格林函数，显著提高了SNR。在本研究中，我们通过模拟和从一艘在100米深浅水中移动的船上收集的宽带噪声数据（200 - 900赫兹）演示了所提出的方法。
