• 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.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.606-614
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• 2020

In this paper, we analyze the influences of ship traffic and marine weather information on underwater ambient noise. Ambient noise is an important environmental factor that greatly affects the detection performance of underwater sonar systems. In order to implement an automated system such as prediction of detection performance using artificial intelligence technology, which has been recently studied, it is necessary to obtain and analyze major data related to these. The main sources of ambient noise have various causes. In the case of sonar systems operating in offshore seas, the detection performance is greatly affected by the noise caused by ship traffic and marine weather. Therefore, in this paper, the impact of each data was analyzed using the measurement results of ambient noise obtained in coastal area of the East Sea of Korea, and public data of nearby ship traffic and ocean weather information. As a result, it was observed that the underwater ambient noise was highly correlated with the change of the ship's traffic volume, and that marine environment factors such as wind speed, wave height, and rainfall had an effect on a specific frequency band.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.390-399
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• 2020

Underwater ambient noise was measured at the eastern and western costal sites of Jeju Island where the water depth was 20 m by a hydrophone moored at mid-depth (10 m) for 4 months. These eastern and western sites were selected as potential sites for offshore wind power generator and the current wave energy generator, respectively. Ambient noise was affected by environmental data such as wind and wave, which were collected from nearby weather stations and an observation station. Below 100 Hz, ambient noise was changed about 5 dB ~ 20 dB due to low and high tide. Below 1 kHz, wave and wind effects were the main source for ambient noise, varying up to 25 dB. Ambient noise was strongly influenced by wave at lower frequency and by wind at higher frequency up to over 1 kHz. The higher frequency range over 10 kHz was influenced by rainfall and biological sources, and the spectrum was measured about 10 dB higher than the peak spectrum level from Wenz curve at this frequency range.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.16 no.3
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• pp.197-201
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• 1983

Underwater ambient noise level was measured at two points near the Youngil Bay. The environmental characteristics depend upon oceanographic conditions of sound propagation ana its implication on the source of ambient noise. Some noise sources were estimated, and the effect of the oceanographic conditions on the noise level variation had been considered. The results were as follows : 1) At the nearshore station of Youngil Bay, the ambient noise level in the near bottom(45m) was lower than that of the near surface(10m) by 15dB. This difference was due to spherical spreading from the upper to the lower layer. 2) At the open sea station which is located outside of the thermal front existing near the Youngil Bay, the ambient noise level of the upper layer(20m) was higher than that of the lower layer (100m) by $8{\sim}12dB$ below 50Hz and $15{\sim}23dB$ above 50Hz. 3) Above 60Hz the ambient noise level at the nearshore station was higher than that of the open sea station, while below 60Hz, the result was reverse. It appears that a boundary layer existed between the two stations.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.71-81
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• 1995

In this paper, feature vector extraction methods and classification algorithms for the automatic classification of transient signals in underwater are discussed. A feature vector extraction method using wavelet transform, which shows good performance with small number of coefficients, is proposed and compared with the existing classical methods. For the automatic classification, artificial neural networks such as multilayer perceptron (MLP), radial basis function (RBF), and MLP-Class are utilized, where those neural networks as well as extracted feature vectors are combined to improve the performance and reliability of the proposed algorithm. It is confirmed by computer simulation with Traco's standard transient data set I and simulated data that the proposed feature vector extraction method and classification algorithm perform well, assuming that the energy of a given transient signal is sufficiently larger than that of a ambient noise, that there are the finite number of noise sources, and that there does not exist noise sources more than two simultaneously.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2E
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• pp.30-45
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• 2001

This study considers the environmental factors affecting propagation loss and sonar performance in the continental regions of the East Coast Sea of Korea. Water mass distributions appear to change dramatically in a few weeks. Simple calculation with the case when the NKCW (North Korean Cold Water) develops shows that the difference in propagation loss may reach in the worst up to 10dB over range 5km. Another factor, an eddy, has typical dimensions of 100-200km in diameter and 150-200m in thickness. Employing a typical eddy and assuming frequency to be 100Hz, its effects on propagation loss appear to make lower the normal formation of convergence zones with which sonars are possible to detect long-range targets. The change of convergence zones may result in 10dB difference in received signals in a given depth. Thermal fronts also appear to be critical restrictions to operating sonars in shallow waters. Assuming frequency to be 200Hz, thermal fronts can make 10dB difference in propagation loss between with and without them over range 20km. An observation made in one site in the East Coast Sea of Korea reveals that internal waves may appear in near-inertial period and their spectra may exist in periods 2-17min. A simulation employing simple internal wave packets gives that they break convergence zones on the bottom, causing the performance degradation of FOM as much as 4dB in frequency 1kHz. An acoustic experiment, using fixed source and receiver at the same site, shows that the received signals fluctuate tremendously with time reaching up to 6.5dB in frequencies 1kHz or less. Ambient noises give negative effects directly on sonar performance. Measurements at some sites in the East Coast Sea of Korea suggest that the noise levels greatly fluctuate with time, for example noon and early morning, mainly due to ship traffics. The average difference in a day may reach 10dB in frequency 200Hz. Another experiment using an array of hydrophones gives that the spectrum levels of ambient noises are highly directional, their difference being as large as 10dB with vertical or horizontal angles. This fact strongly implies that we should obtain in-situ information of noise levels to estimate reasonable sonar performance. As one of non-stationary noise sources, an eel may give serious problems to sonar operation on or under the sea bottoms. Observed eel noises in a pier of water depth 14m appear to have duration time of about 0.4 seconds and frequency ranges of 0.2-2.8kHz. The 'song'of an eel increases ambient noise levels to average 2.16dB in the frequencies concerned, being large enough to degrade detection performance of the sonars on or below sediments. An experiment using hydrophones in water and sediment gives that sensitivity drops of 3-4dB are expected for the hydrophones laid in sediment at frequencies of 0.5-1.5kHz. The SNR difference between in water and in sediment, however, shows large fluctuations rather than stable patterns with the source-receiver ranges.

• The Journal of the Acoustical Society of Korea
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• v.34 no.6
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• pp.411-422
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• 2015

This paper presents an overview of the geological environment investigation and underwater acoustic measurements for the purpose of "Study on the Relationship between the Geological Environment and Acoustic Propagation in Shallow Water", which are jointly carried out by KIOST (Korea Institute of Ocean Science & Technology) and Hanyang University in the western shallow water off the Taean peninsula in the Yellow Sea in April-May 2013. The experimental site was made up of various sediment types and bedforms due to the strong tidal currents and coastal geomorphological characteristics. The geological characteristics of the study area were intensively investigated using multi-beam echo sounder, sub-bottom profiler, sparker system and grab sampler. Acoustic measurements with a wide range of research topics in a frequency range of 20~16,000 Hz: 1) low frequency sound propagation, 2) mid-frequency bottom loss, 3) spatial coherence analysis of ambient noise, and 4) mid- frequency bottom backscattering were performed using low- and mid-frequency sound sources and vertical line array. This paper summarizes the topics that motivated the experiment, methodologies of the acoustic measurements, and acoustic data analysis based on the measured geological characteristics, and describes summary results of the geological, meteorological, and oceanographic conditions found during the experiments.