• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.330-336
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• 2021

In bistatic sonar operation, the scattering strength of a sonar target is characterized by the probe signal frequency, the aspect angle and the bistatic angle. Therefore, the target detection and identification performance of the bistatic sonar may vary depending on how the positions of the target, sound source, and receiver are changed during sonar operation. In this study, it was evaluated which variable is advantageous to change by comparing the target identification performance between the case of changing the aspect angle and the case of changing the bistatic angle during the operation. A scenario of identifying a hollow sphere and a cylinder was assumed, and performance was compared by classifying two targets with a support vector machine and comparing their accuracy using a finite element method-based acoustic scattering simulation. As a result of comparison, using the scattering strength defined by the frequency and the bistatic angle with the aspect angle fixed showed superior average classification accuracy. It means that moving the receiver to change the bistatic angle is more effective than moving the sound source to change the aspect angle for target identification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.579-585
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• 2019

Increasing the detection probability of underwater targets necessitates securing the towing stability of the active towed SONAR. In this paper, to confirm the effects of tail wing fin on towing attitude and towing stability, two scale model experiments and one sea trials were conducted and the results were analyzed. The scale model tests measured the towing behavior of each of the tail fin shapes according to towing speed in a towing tank. The shape of the tail fin used in the scale model test was tested with an I-type tail fine and four Y-type tail fins, totaling five tail fins of the two kinds. The first scale model test confirmed that the Y-type tail fin was superior to the I-type tail fin in towing attitude and towing stability. The second scale model test confirmed the characteristics of the vertical tail fin height increase and the lower horizontal tail fin inclination angle application shape based on the Y-type tail fin. The shape of the application of the lower horizontal tail fin inclination angle showed the best performance. In order to verify the results of the scale model test, a full size model was constructed, sea trials were performed, and the towing attitude was measured. The results were similar to those of the scale model test.

• Geophysics and Geophysical Exploration
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• v.26 no.1
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• pp.8-17
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• 2023

Various sources, such as wind, waves, ships, and gas leaks from the seafloor, forms bubbles in the ocean. Underwater bubbles cause signal scattering, considerably affecting acoustic measurements. This characteristic of bubbles is used to block underwater noise by attenuating the intensity of the propagated signal. Recently, researchers have been studying the large-scale release of methane gas as bubble plumes from the seabed. Understanding the physical properties and distribution of bubble plumes is crucial for studying the relation between leaked methane gas and climate change. Therefore, a water tank experiment was conducted to estimate the distribution of bubble plumes using seismic imaging techniques and acoustic signals obtained from artificially generated bubbles using a bubble generator. Reverse time migration was applied to image the bubble plumes while the acquired acoustic envelope signal was used to effectively estimate bubble distribution. Imaging results were compared with optical camera images to verify the estimated bubble distribution. The water tank experiment confirmed that the proposed system could successfully image the distribution of bubble plumes using reverse time migration and the envelope signal. The experiment showed that the scattering signal of artificial bubble plumes can be used for seismic imaging.

• Geophysics and Geophysical Exploration
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• v.26 no.3
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• pp.126-137
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• 2023

In this study, a recurrent neural network (RNN) was employed as a methodological approach to classify dolphin click signals derived from ocean monitoring data. To improve the accuracy of click signal classification, the single time series data were transformed into fractional domains using fractional Fourier transform to expand its features. Transformed data were used as input for three RNN models: long short-term memory (LSTM), gated recurrent unit (GRU), and bidirectional LSTM (BiLSTM), which were compared to determine the optimal network for the classification of signals. Because the fractional Fourier transform displayed different characteristics depending on the chosen angle parameter, the optimal angle range for each RNN was first determined. To evaluate network performance, metrics such as accuracy, precision, recall, and F1-score were employed. Numerical experiments demonstrated that all three networks performed well, however, the BiLSTM network outperformed LSTM and GRU in terms of learning results. Furthermore, the BiLSTM network provided lower misclassification than the other networks and was deemed the most practically appliable to field data.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.10-18
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• 2009

A moving surface vessel generates a ship wake which contains a cloud of micro-bubbles with radii ranging between $8{\sim}200{\mu}m$. Such micro-bubbles can be detected by active sonar system for more than ten minutes depending on the size and speed of the surface vessel. In this paper, a reverberation model for the ship wake is presented. The developed model consists of the acoustic scattering model due to the distribution of the micro-bubbles and the kinematic model for the moving active sonar. The acoustic scattering model is based on the volume integration, where the volume scattering strengths are obtained from the spatial distribution of micro-bubbles. Since the directivity and look-direction of active sonar are important factors for moving active sonar, the kinematic model utilizes the Euler transformation to obtain the relative motion between the global and local coordinates. In order to verify the developed model, a series of sea experiment was executed in September 2007 to obtain the spatial-temporal distribution of a bubble cloud, and analyzed to be compared with the simulation results.