• Journal of Ocean Engineering and Technology
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• v.22 no.1
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• pp.30-36
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• 2008

Underwater ambient noise originating from geophysical, biological, and man-made acoustic sources contains information on the source and the ocean environment. Such noise affectsthe performance of sonar equipment. In this paper, three steps are used to identify the ambient noise source, detection, feature extraction, and similarity measurement. First, we use the zero-crossing rate to detect the ambient noisesource from background noise. Then, a set of feature vectors is proposed forthe ambient noise source using the Hilbert-Huang transform and the Karhunen-Loeve transform. Finally, the Euclidean distance is used to measure the similarity between the standard feature vector and the feature vector of the unknown ambient noise source. The developed algorithm is applied to the observed ocean data, and the results are presented and discussed.

• Ocean Science Journal
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• v.41 no.3
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• pp.175-179
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• 2006

The Ieodo Ocean Research Station(IORS) is an integrated meteorological and oceanographic observation base which was constructed on the Ieodo underwater rock located at a distance of about 150 km to the south-west of the Mara-do, the southernmost island in Korea. The underwater ambient noise level observed at the IORS was similar to the results of the shallow water surrounding the Korean Peninsula (Choi et al. 2003) and was higher than that of deep ocean (Wenz 1962). The wind dependence of ambient noise was dominant at frequencies of a few kHz. The surface current dependence of ambient noise showed good correlation with the ambient noise in the frequency of 10 kHz. Especially, the shrimp sound was estimated through investigations of waveform and spectrum and its main acoustic energy was about 40 dB larger than ambient noise level at 5 kHz.

• Ocean and Polar Research
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• v.28 no.4
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• pp.459-465
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• 2006

Ambient noise as a background noise in the ocean has been well known for its the various and irregular signal characteristics. Generally, these signals we treated as noise and they are analyzed through stochastical level if they don't include definite sinusoidal signals. This study is to see how ocean ambient noise can be analyzed by the chaotic analysis technique. The chaotic analysis is carried out with underwater ambient noise obtained in areas near the Korean Peninsula. The calculated physical parameters of time series signal are as follows: histogram, self-correlation coefficient, delay time, frequency spectrum, sonogram, return map, embedding dimension, correlation dimension, Lyapunov exponent, etc. We investigate the chaotic pattern of noises from these parameters. From the embedding dimensions of underwater noises, the assesment of underwater noise by chaotic analysis shows similar results if they don't include a definite sinusoidal signal. However, the values of Lyapunov exponent (divergence exponent) are smaller than that of random noise signal. As a result we confirm the possibility of classification of underwater noise using Lyapunov analysis.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.307-310
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• 2006

Underwater ambient noise originating from the geophysical, biological, and man-made acoustic sources contains much information on the sources and the ocean environment affecting the performance of the sonar equipments. In this paper, a set of feature vectors of the ambient noises using MFCC is proposed and extracted to form a data base for the purpose of identifying the noise sources. The developed algorithm for the pattern recognition is applied to the observed ocean data, and the initial results are presented and discussed.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.57-63
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• 2012

In this paper, a Bayesian classifier based on PCA (principle component analysis) is proposed to classify underwater transient signals using $16^{th}$ order LPC (linear predictive coding) coefficients as feature vector. The proposed classifier is composed of two steps. The mechanical signals were separated from biological signals in the first step, and then each type of the mechanical signal was recognized in the second step. Three biological transient signals and two mechanical signals were used to conduct experiments. The classification ratios for the feature vectors of biological signals and mechanical signals were 94.75% and 97.23%, respectively, when all 16 order LPC vector were used. In order to determine the effect of underwater noise on the classification performance, underwater ambient noise was added to the test signals and the classification ratio according to SNR (signal-to-noise ratio) was compared by changing dimension of feature vector using PCA. The classification ratios of the biological and mechanical signals under ocean ambient noise at 10dB SNR, were 0.51% and 100% respectively. However, the ratios were changed to 53.07% and 83.14% when the dimension of feature vector was converted to three by applying PCA. For correct, classification, it is required SNR over 10 dB for three dimension feature vector and over 30dB SNR for seven dimension feature vector under ocean ambient noise environment.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.397-409
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• 2022

A model is developed for the calculation of sea surface generated ambient noise in the range dependent ocean environment. The sources are located in the horizontal plane all around and their depths are at the near-surface. The receiver array is located in the range dependent ocean waveguide. One-way coupled mode method is used to model the acoustic propagation between the sources and receiver in the range dependent waveguide, and the cross spectral density matrix of noise is derived. In simulation, noise intensity, beamforming result and coherence function are calculated from the cross spectral density matrix. These results are compared with those in the range independent environment. The modeling result shows the effect of the vertical directionality and asymmetry characteristics of the horizontal plane.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.21 no.1
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• pp.7-11
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• 1985

Underwater ambient noise in the depth 5m to 200m layers was measured at 14 point from the 24th of July to 2nd of August, 1984, in the Korean east sea areas. The underwater ambient noise pressure level was depended upon configuration of the sea bottom and sea condition, which was formed type of prevaling noise at a long distance from coast and type of intermittent and regional noise at a short distance from coast.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.340-348
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• 2016

Ray-based model for the calculation of the ocean surface-generated ambient noise coherence function has the form of double integral with respect to a range and a bearing angle. While the theoretical consideration about its numerical implementations was partly given in the past work of authors, the numerical results on the ocean environment have not been presented yet. In this paper, we perform numerical experiments for shallow and deep water environments. It is shown that the coherence function depends on the ocean sediment sound speed, and is more sensitive to the ocean sediment sound speed in the shallow water than in the deep water. Similar trend is also observed for varying the orientation of hydrophone pair. In addition, a post-processing technique is proposed in order to plot the noise intensity for the noise receiving angle. This procedure will supplement the weakness of the ray-based model about the output data type compared to the semi-analytic model of Harrison.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.142-146
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• 2007

Ambient noise was measured for 3 hours on May, 2001 at a site of 20 m water depth in the Korean coast of the Yellow Sea. During the measurement, the strong underwater sound assuming by marine life was continually observed. The spectrum level of this sound was very high compared to that of underwater ambient noise over the frequency range from 1 to 20 kHz. Therefore, this underwater sound can continually affect the ambient noise level. In this study, the source of the underwater sound was investigated. The snapping shrimp was estimated as reliable source. It was confirmed through comparison with experimental results described in previously literatures. It was also confirmed through analysis of snapping shrimp sound measured under laboratory conditions.

• The Journal of the Acoustical Society of Korea
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• v.34 no.3
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• pp.200-209
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• 2015

An underwater sound surveillance system detects and tracks enemy ships in real-time using hydrophone arrays, in which seabed-mounted sensor arrays play a pivotal role. In this paper the conceptual design of seabed-mounted, cylindrical hydrophone arrays for use in shallow coastal waters is performed via finite element calculations. To stabilize the receiving characteristics under the ocean ambient noise, a technique for whitening the ambient noise spectrum using a metal baffle is proposed. Optimization of the array configuration is performed to achieve the directivity in the vertical and azimuthal directions. And the effects of the sonar dome shape and material on the structural vibration and sound scattering properties are studied. It is demonstrated that a robust hydrophone array, having a sensitivity deviation less than 4 dB over the frequency range of interest, can be obtained through the whitening of the ambient noise, the optimization of the array configuration, and the design of acoustically transparent sonar domes.