• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.428-436
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• 2004

Synthetic Aperture Sonar is a technique of extending Physically limited length of an array by signal processing to enhance bearing resolution of a system. The previous techniques estimate most or away shapes as linear. so when towed array shapes are distorted. this can create a deviation from actual situation. In this paper. we estimated perturbed away shapes. and compensated distortion by using estimated array shapes and synthesized arrays in aperture domain. As experimental data, we used the one obtained from towed array in neighboring waters of the Korean peninsula. We extended array by compensating differences in time and spatial position between overlapped subarrays by using SAS techniques. In simulation results. we confirmed that the bearing resolution was enhanced.

• The Journal of the Acoustical Society of Korea
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• v.19 no.4
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• pp.77-83
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• 2000

The previous synthetic aperture techniques have been investigated to increase signal gain, improve angular resolution and peak-to-sidelobe level ratios for towed line array sonar systems. The synthetic aperture method in this paper is performed for conformal array systems by mapping real elements on an axis to control like a linear array. The proposed method for the conformal array performs coherent processing of subaperture signals at successive time intervals in the beam domain via FFT transformations. This was confirmed by the simulation results and compared to the results from use of the synthetic aperture technique under the conformal array.

• Journal of Ocean Engineering and Technology
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• v.34 no.5
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• pp.371-376
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• 2020

Underwater acoustics, which is the study of the phenomena related to sound waves in water, has been applied mainly in research on the use of sound navigation and range (SONAR) systems for communication, target detection, investigation of marine resources and environments, and noise measurement and analysis. Underwater acoustics is mainly applied in the field of remote sensing, wherein information on a target object is acquired indirectly from acoustic data. Presently, machine learning, which has recently been applied successfully in a variety of research fields, is being utilized extensively in remote sensing to obtain and extract information. In the earlier parts of this work, we examined the research trends involving the machine learning techniques and theories that are mainly used in underwater acoustics, as well as their applications in active/passive SONAR systems (Yang et al., 2020a; Yang et al., 2020b; Yang et al., 2020c). As a follow-up, this paper reviews machine learning applications for the inversion of ocean parameters such as sound speed profiles and sediment geoacoustic parameters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.1878-1883
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• 2012

Generally, in the underwater target recognition, feature vectors are extracted from the target signal utilizing spatial information according to target shape/material characteristics. And, various signal processing techniques have been studied to extract feature vectors which is less sensitive to the location of the receiver. In this paper, we analyzed the characteristics of synthesized underwater objects using canonical correlation analysis method which is relatively less sensitive to the location of receiver. Canonical correlation analysis is applied to two consecutive backscattered sonar returns at different aspect angles to analyze the correlation characteristics in multi-aspect environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.915-920
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• 2007

Using the existing algorithms that estimate the background noise, the detection probability for the week tonals is low and for the even week tonals, there is a limit not detected. Therefore it is required to algorithms which can improve the performance of the tonal extraction. Recently, many researches using artificial neural networks in sonar signal processing are performed. We propose a neural network with double feedback that can remove automatically the background noise and detect the even week tonals buried in background noise, therefore not detected by growing the week tonals lastingly for a certain time. For the real underwater target, experiments for the tonal extraction are performed by using the existing algorithms that estimate the background noise and the proposed neural network. As a result of the experiment, a method using the proposed neural network showed the better performance of the tonal extraction in comparison with the existing algorithms.

• 한국해양학회지
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• v.22 no.3
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• pp.143-152
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• 1987

The digital data were obtained using Kennedy 9000 magnetic tape deck which was connected to the SMS960 side scan sonar during the field operations. The data of three consecutive survey tracks near Seongsan-po, Cheju were used for the development of this study. The softwares were mainly written in Fortran-77 using VAX 11/780 MINI-COMPUTER (CPU Memory; 4MB). The established mapping system consists of the pretreatment and the digital processing of seafloor image data. The pretreatment was necessary because the raw digital data format of the field magnetic tapes was not compatible to the VAX system. Therefore the raw data were read by the personal computer using the Assembler language and the data format was converted to IBM compatible, and next data were communicated to the VAX system. The digital processing includes geometrical correction for slant range, statistical analysis and cartography of the seafloor image. The sound speed in the water column was assumed 1,500 m/sec for the slant range correction and the moving average method was used for the signal trace smoothing. Histograms and cumulative curves were established for the statistical analysis, that was purposed to classify the backscattering strength from the sea-bottom. The seafloor image was displayed on the color screen of the TEKTRONIX 4113B terminal. According to the brief interpretation of the result image map, rocky and sedimentary bottoms were very well discriminated. Also it was shown that the backscattered acoustic pressurecorrelateswith the grain size and sorting of surface sediments.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.643-646
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• 1998

소나 시스템과 같이 방대한 양의 연산을 요구하는 고속 신호처리기를 구현하기 위해서는 상용 DSP 칩의 병렬 처리방법은 필요 불가결하다. 본 논문에서는 TI사의 TMS320C40을 이용한 병렬 신호 처리 시스템을 소개한다. TI사의 TMS320C40을 이용한 소나 시스템 신호처리부의 기본 모델을 제시하고, TI에서 제공하는 FFT구현 소스의 분석을 통한 연산의 수학적인 모델을 제시하고 이를 근거로 제안된 모델의 성능을 분석하였다.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.558-563
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• 1992

Bearing information of target is used critically for target tracking in underwater environment. In passive sonar, target bearing measurements are obtained by processing the acoustic signal emanating from the target. PDA tracking algorithm is usually applied in this case since bearing measurements have several peaks due to interference with other acoustic sources or reflections from underwater media. In this paper, we propose a modified PDA algorithm adopting new probabilistic distributions of the number, position, and amplitude of peaks based on the analysis of real data. This algorithm is tested on real and artificially generated data. The computer simulation result shows improvement of the tracking performance.

• The Journal of the Acoustical Society of Korea
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• v.4 no.1
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• pp.22-34
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• 1985

소나 신호 처리에서, 흔히 발생하는 난반사에 의한 잡음 때문에, 기존에 사용되어지고 있는 앨고 리즘으로 처리하기에는 많은 문제점을 내포하고 있다. 본 연구는 소나 시스템의 신호 처리를 위하여 마 이크로 프로세서를 사용하였으며, 신호처리 방법은 코릴레이숀 접음과 반사음을 식별하고, 거기서 평가 된 것을 기준으로 직접음만의 신호를 재생하여 반사음을 처리하였다. 실험의 결과치와 계산치를 비교한 결과, 무향 수조의 특성에 의한 오차를 제외하고는 거의 오차가 없었으며, 그 오차는 주파수가 낮아짐에 따라 증가하였다. 실험 결과를 토대로 처리 시스템의 소형·단순화가 가능한 것으로 분석되었다.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.172-180
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• 2012

In multi-static sonar for detecting an underwater target, received signals contain the target echo, reverberation and clutter. Clutter and reverberation are main causes of increasing the false alarm rate. MRAL classifies received signals according to the spatial similarity, and it regards classified signal as reflected signals from a reflector. MRAL reduces the false alarm rate this way. However, the results of MRAL can have localization errors. In this paper, an MRAL post processing algorithm is proposed to reduce the localization errors with the least square (LS) method.