• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2753-2758
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• 2009

The Navy is trying to develop a sonar-operation strategy that efficiently searches for underwater targets. To develop an efficient sonar-operation strategy, a simulation system, which can analyze the efficiency of various operation strategies, is needed. The simulation executes the strategical operation by collecting information of sea environment, destroyer, sonar, and target. Also, it should be able to provide diverse information according to its progression. In this study, the simulation system that can evaluate and analyze the effectiveness of the search strategy for underwater targets in different environments was designed and developed. The simulation system was developed, utilizing the sonar equation and the lateral-range-curve, and it portrays many patterns of realistic movements of a target. This system will contribute to developing and improving efficient sonar-operation strategies to find underwater targets in the future.

• The Journal of the Acoustical Society of Korea
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• v.19 no.7
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• pp.15-22
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• 2000

This paper proposes a distributed highlight algorithm to generate efficiently echo signal for underwater target. In this algorithm, echo signal is synthesized by discontinuity highlights that are varied to incident angle, by equivalent and specified position highlights according to the spatial target structure. Completed UTAHID(Underwater TArget by Highlight Distribution) model is confrimed that PTS, ETS, echo elongation effect, target time spreading loss and envelope fluctuation are satisfied to expected values by various simulations. Thus it can be efficiently used in all sorts of real systems related to underwater target echo signal synthesis in active sonar.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.293-299
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• 2017

Small unmanned platforms maneuvering underwater are the key naval future forces, utilized as the asymmetric power in war. As a method of detecting and identifying such platforms, we introduce a property estimation technique based on an iterative numerical analysis. The property estimation technique can estimate not only the position of a target but also its physical properties. Moreover, it will have a potential in detecting and classifying still target or multiple targets. In this study, we have conducted the property estimation of an small underwater target using the data acquired from the lake experiment. As a result, it shows that the properties of a small platform may be roughly estimated from the in site data even using one channel.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.44-51
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• 2001

This Paper the practical echo signal synthesis model to predict the target strength and signal shape of a submarine for a valuable tool to active sonar engineer. It is based on UTAHID (Underwater TArget by Highlight Distribution) model which is relocated highlight points along to external hull for aspect angle, and synthesized echo signal by modified grouping highlights to internal scatter cloud. Proposed model is analyzed target strength characteristics on various incident pulse length, and synthesis signal signature, target time spreading loss, echo elongation effect and so on. Thus it can be efficiently used in various real systems related to underwater target echo signal synthesis, that is, active sonar, acoustic countermeasure and surveillance system.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.27 no.3
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• pp.149-153
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• 2008

General underwater target detection methods adopt short-time FFT for estimate target doppler. This paper proposes the efficient target detection method, instead of conventional FFT, using approximate FFT for distributed sensor network target detection, which requires lighter computations. In the proposed method, we decrease computational rate of FFT by the quantization of received signal. For validation of the proposed method, experiment result which is applied to FFT based active sonar detector and real oceanic data is presented.

• The Journal of the Acoustical Society of Korea
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• v.15 no.6
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• pp.104-109
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• 1996

In passive sonar system, frequency lines generated by underwater target are very important for detection, tracking and classification. In this paper, the extraction method of unstable frequency line from the time samples of the radiated noise of underwater target is studied. As unstable frequency line is time varying, an extended Kalman filter algorithm which is desirable for nonlinear system is applied to extract unstable frequency line. The proposed method shows good extraction of unstable frequency line by application of simulated signal and real target.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.6-14
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• 1996

In this paper we present an algorithm to discriminate an underwater target under track against an acoustic counter-measure(ACM) source, based on a sequential hypothesis test. The ACM source is separated from the target under track and generates, while drifting, measurements with false range and Doppler information. The purpose of the ACM is to mislead the target-tracking and to help the true target evade a pursuer. The algorithm uses as a test statistic a function of the innovation sequences from extended Kalman filters to estimate the target dynamics and the drifting position of the ACM source. Numerical experiments on various scenarios show that the proposed algorithm discriminates the target against an ACM source very fast with a high probability of success.

• Proceedings of the Acoustical Society of Korea Conference
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• 1996.06a
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• pp.22-28
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• 1996

수동 소나 시스템에서 표적을 탐지, 식별하는데 가장 중요한 인자는 표적에서 발생되는 토날 신호 성분이다. 수중의 주변잡음과 표적소음이 복합된 환경하에서 표적의 토날 신호성분을 정확히 추출하는데는 신호 탐지 준위 설정이나 주변 잡음의 변화에 의해 어려움이 있다. 본 논문에서는 ASM 신경망을 이용하여 신호 탐지 준위 설정이나 주변잡음의 변화에 강인한 음향 표적의 토날 신호 탐지 방식을 제안한다. 모의 시뮬레이션 및 실제 표적 신호에 적용하여 우수한 토날 신호 탐지 성능을 보인다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.22-29
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• 2016

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target detection technique has been considered as a difficult technique. In this paper, we describe the basic concept of Fractional Fourier transform and optimal transform order. Then we analyze the relationship between time-frequency characteristics of an LFM signal and its spectrum using Fractional Fourier transform. Based on the analysis results, we present active sonar target detection method. To verify the performance of proposed methods, we compared the results with conventional FFT-based matched filter. The experimental results demonstrate the superiority of the proposed method compared to the conventional method in the aspect of AUC(Area Under the ROC Curve).