内孤立波是一种常见于浅海海域的非线性内波, 具有振幅大、周期短和流速强等特点, 它通过扰动水体中的温盐分布使声速剖面产生明显的距离依赖性, 进而影响水下声传播特性. 内波自生成后通常以 \begin{document}$ O(1) $\end{document} m/s 量级的速度传播, 运动的内波使声传播路径上的声波模态能量在空间和时间上剧烈起伏. 本文定义模态强度为模态系数模值 (模态幅度) 的平方, 并用其衡量各阶模态所含声能量的大小. 文中基于耦合简正波理论, 推导了内波运动时声波模态强度起伏的表达式, 将模态强度表征为振荡项和趋势项的线性叠加. 以往的工作大多局限于单独从时域或频域研究内波运动时声波模态强度的时变规律, 本文则结合短时傅里叶变换在时频平面上揭示了模态强度的起伏机理. 理论推导和数值仿真均表明内孤立波使各阶声波模态之间发生能量交换, 即模态耦合. 内波的动态传播进一步引起模态干涉, 这种干涉效应表现为模态强度中的振荡项并使模态强度随时间快速起伏. 受模态剥离效应 (不同阶模态之间衰减系数的差异) 的影响, 趋势项的幅度随时间不断变化, 进而对模态干涉引起的振荡叠加了时变的偏置. 模态强度的整体走势和振荡项中各频率分量振幅的时变特征均与模态衰减密切相关. 同时, 本文使用深度积分声强作为总接收声场强度的度量, 研究了内波运动时模态强度起伏对接收阵位置处声能量的影响. 结果表明, 能量较大且起伏剧烈的模态强度将主导总接收声强的变化.

In underwater radiated noise measurement using a vertical linear array, a diagonalization-decorrelation-based diagonal denoising method is proposed to improve the denoising effect for spatially correlated noise. Firstly, the ambient noise cross-spectral matrix is measured without the radiated noise source. Subsequently, the eigenvector matrix of the ambient noise cross-spectral matrix is utilized to implement a unitary transformation for the received data, which eliminates the correlation of the received noise and transforms the received noise cross-spectral matrix into a diagonal matrix, then the noise components are removed by diagonal denoising. Finally, the denoised cross-spectral matrix is used to estimate the power of the radiated noise by beamforming. Consequently, the influence of spatially correlated noise on radiated noise measurement is reduced. The effectiveness of the proposed method is validated and compared with the diagonal denoising method and the whitening-decorrelation-based diagonal denoising method via numerical simulations and experimental data. Under the ideal condition, the noise reduction performances of the proposed method and the whitening-decorrelation-based diagonal denoising method are equal and better than that of the diagonal denoising method. In practice, the number of snapshots is limited, so there is an inevitable mismatch between the ambient noise cross-spectral matrix and the received noise cross-spectral matrix due to the randomness of noise. The mismatch results in imperfect whitening and diagonalization, which reduces the denoising effect. However, the simulation results indicate that the proposed method still reduces more correlated noise and has a better performance on underwater radiated noise measurement compared with the diagonal denoising method and the whitening-decorrelation-based diagonal denoising method even if the number of snapshots is finite.

Internal solitary waves evolving with time in shallow water are known to affect sound propagation significantly. Unlike prior work studying the acoustic effects of individual internal-wave properties separately, this paper elucidates and evaluates the influence of a complete evolution process of internal waves on acoustic fields both theoretically and by the coupled ocean-acoustic simulation. Two evolving wave properties considered here are shape deformations including the variations of wave amplitudes and widths and packet dispersion manifested as the increasing wavelength (i.e., the distance between successive solitons). The acoustic modal intensity expressed by the Dyson series solution is reformulated to explicitly reveal the modulation effects induced by the deformation and dispersion of internal waves. Dispersion leads to modal interference and causes the intensity envelope to oscillate with the varying wavelength. Deformation modulates intensity in a non-oscillatory manner that is less predictable due to the complexity of amplitude and width variations. In the environment reconstructed from the field observations of internal waves in the South China Sea, the modal intensity simulated by the parabolic-equation model exhibits pronounced modulation effects, where the modal interference due to dispersion dominates the intensity-envelope shape, and deformation affects the extremum positions of envelopes.

Array gain is investigated based on the acoustic channel characteristics manifested by the fluctuant transmission loss and decrease in the acoustic channel spatial coherence. An analytical expression is derived as the summation of the products of the acoustic channel correlation coefficients and root-mean-square pressures. The formula provides insight into the physical mechanisms of the gain degradation in the ocean waveguide. Furthermore, this formula provides a new method to study array gain in the ocean waveguide from underwater acoustic field. The obtained expression is a more general formula that is applicable to shallow water, deep sea, and continental slope, with the traditional methods as a special case. Numerical results show that the array gain calculated by previous formulas are generally overestimated, caused by ignoring the effect of transmission loss fluctuation.

Environmental mismatch degrades the performance of source localization and tracking methods in shallow water. One solution is to estimate source parameters and the key environmental parameters simultaneously from the acoustic data. In this paper, an unconventional approach of joint tracking source depth and water depth parameters by a particle filter is proposed. This approach is free of prior environmental knowledge and numerical calculation of any forward model. First, a state-space model based on modal nature behavior is established driving the shallow-water propagation, instead of modeling in time or space, as was done previous works. Subsequently, particle filtering is employed for joint tracking, in which the evolution with mode-order of vertical wavenumbers and the relationship between state parameters and beam-wavenumber outputs transformed from the data are exploited. Final, the particle smoother reduces the uncertainty of state parameters at initial steps, and improves the overall tracking accuracy. Our approach is demonstrated using simulated data in an ideal waveguide and applied to shallow-water SWellEx-96 experimental data to substantiate its superior performance.

Horizontal coherence length informs array aperture design and coherent processing performance assessment. This study presents a method for measuring horizontal coherence length along an array in the presence of interference and background noise. Subarray beamforming suppresses interference from non-target bearings. Effective degrees of freedom (EDOF) and eigenvalue difference entropy (EDE) are constructed from the eigenvalue difference spectrum of the cross-spectral density matrix to reduce the effect of an approximately common noise contribution to the eigenvalues. Numerical mappings to coherence length are established for three spatial coherence functions, accounting for subarray processing effects on signal and noise correlations. At the lower signal-to-noise ratios examined, simulations show that mean EDOF and EDE estimates are generally closer to the true values than power factor (PF) and eigenvalue ratio (ER) estimates, despite correlated noise introduced by subarray processing. Measurements from a convergence zone in the deep western Pacific show that, at higher signal-to-noise ratios, the estimates are comparable in magnitude to PF and ER estimates and exhibit broadly consistent frequency trends, supporting the method’s effectiveness. The estimates vary with time and frequency, and their scale depends on the coherence function model and decay parameter.