Ocean reverberation is an important issue in underwater acoustics, which usually influences the working performance of the active sonars significantly. The deep-water reverberation data are collected from the South China Sea experiment including the reverberation signals at large receiving depths near the bottom, showing that the wave intensity increases obviously at some moments with time increasing. To analyze in depth the data, a uniform bottom-reverberation model is proposed based on the ray theory, which can calculate monostatic and bistatic reverberation intensity and explain the generation process of deep-water reverberation. The mesh method is first used in this model by dividing bottom scatterers into a number of grids. Then reverberation is calculated based on the exact time of generating the scattering signal from each grid. Due to the exact arrival time, the presented model can provide more accurate result than classical models, in which scatterers are usually treated as circular rings or elliptical rings. Numerical results are compared with experimental reverberations at different receiving distances and depths. The simulated and experimental results agree well overall for large receiving depths, whereas agreement extent decreases for the case of receiving depth close to the sea surface. The analytical results indicate that the applied scattering coefficient is suitable for this experimental sea area, and meanwhile verify that this scattering model is more accurate for low-angle bottom backscatters corresponding to the reverberation at large receiving depths.
The sound field temporal correlation and spatial correlation, which are the foundation of the investigation of underwater signal space-time high-order characteristics, have important value in the underwater acoustic application. The spatial correlation is studied based on the shallow water acoustic propagation experiment data acquired in the northern South China Sea in 2017, and the deep water acoustic propagation experiment data acquired in the western Pacific in 2013. As for the explosive sound signals in shallow water, time domain waveform cross-correlation coefficients between signals from different propagation distance are calculated. In contrast, the linear frequency modulated signals in deep water need additional matched filtering. The signal processing results shows that, the overall spatial correlation is poor and the correlation radius is relatively small in shallow water, the convergence zone has an obviously better spatial correlation than the shadow zone for the deep water situation. The processing result is verified by simulation and analysis.
An ocean acoustic tomography (OAT) experiment conducted in the northern South China Sea in 2021 measured a month-long record of acoustic travel times along paths of over one hundred kilometers in range. A mesoscale eddy passed through the experimental region during the deployment of four acoustic moorings, providing unique OAT data for examining the deep temperature change in the eddy and for comparison with the Hybrid Coordinate Ocean Model (HYCOM) data. The existence of the eddy is first confirmed by the merged sea level anomaly (MSLA) image and HYCOM data and it can exceed the depth of the sound channel axis. The temperature changes measured by temperature and depth (TD)/conductivity–temperature–depth (CTD) loggers and by the OAT sound speed are in accordance with those reflected on the MSLA image during the movement of the eddy. However, the eddy movement prompted by temperature changes in the HYCOM data is different from that measured by TD/CTD. The modeled eddy intensity is at least two times less than the measured eddy intensity. At the sound channel axis depth, a factor of approximately 4.17 ms−1 °C−1 can be used to scale between sound speed and temperature. The transmission/reception path-averaged temperature of the eddy derived from the OAT-computed sound speed at the depth of the sound channel axis is five times greater than those in the HYCOM data. OAT is feasible as a tool to study mesoscale eddy properties in the deep ocean, while HYCOM data are not accurate enough for this mesoscale eddy at the sound channel axis depth. It is suggested that the model be refined by the OAT path-averaged temperature as constraints when the HYCOM data capture the mesoscale eddies.
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