• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.632-637
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• 2008

In real system application, the propeller shaft rate (PSR) estimation algorithm for the feature extraction of the sonar target operates with the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family composed of the fundamental and its harmonics from the multiple spectral lines in the frequency spectrum-based sonar target classification, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. To verify the performance of the proposed algorithm, a sonar target PSR estimation is performed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.524-532
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• 1997

수중음향표적 특히 선박방사소음을 탐지하거나 식별하는 군사적 목적의 수동소나는 수중청음기 배열로 구성되며 각 배열센서에 수신된 신호에 배열 신호처리기술을 적용하여 선박의 거리, 방위 탐지는 물론 선박의 음향적 특징을 식별하는 고도의 음향장치이다. 그러나 이러한 장치운용자의 선박탐지, 식별이나 새로운 수동소나 개발, 나아가 스텔스 능력의 선박 설계를 위해서는 선박방사소음의 측정, 분석 및 예측에 관한 이해가 선행되어야 할 것이다. 본 연구는 대표적인 선박방사소음 측정시스템의 소개, 방사소음발생기구, 측정자료의 분석 및 예측에 관한 기초기술을 연구 분석한 내용이다.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.35 no.2
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• pp.110-117
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• 2016

Passive sonar systems detect and classify the target by analyzing the radiated noises from vessels. If multiple noise sources exist within the sonar detection range, it gets difficult to classify each noise source because mixture of noise sources are observed. To overcome this problem, a beamforming technique is used to separate noise sources spatially though it has various limitations. In this paper, we propose a new method that uses a FDICA (Frequency Domain Independent Component Analysis) to separate noise sources from the mixture. For experiments, each noise source signal was synthesized by considering the features such as machinery tonal components and propeller tonal components. And the results of before and after separation were compared by using LOFAR (Low Frequency Analysis and Recording), DEMON (Detection Envelope Modulation On Noise) analysis.

• Journal of KSNVE
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• v.8 no.2
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• pp.232-238
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• 1998

선박 방사소음은 군사적 목적의 수동소나가 탐지대상으로 하는 수중음향 표적이라 할 수 있다. 따라서 수동소나 운용자는 대잠전 수행이전에 다양한 선박들에 대한 방사소음을 측정, 분석하여 개별 선박 고유의 음향 특징을 수집함으로써 실전 상황에서 미지 선박이 탐지되는 경우 이들 자료를 식별의 기초자료로 활용하고자 한다. 또한 새로운 수동소나의 개발자나 스텔스 능력의 선박 설계자 역시 선박방사소음 특징자료를 필요로한다. 본 글은 선박방사소음의 발생기구, 측정시스템 및 측정자료의 분석 평가 기술을 연구분석한 내용이다.

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.549-557
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• 2019

The acoustical scattering characteristics of a target are influenced by the material properties and structural characteristics of the target, which are critical information for acoustic detection and identification of underwater target. In particular, for thin elastic target, unique scattered signals are generated around the target by the Lamb wave. In this paper, the results of scattered signal measurement of aluminum spherical shell in the water tank using the stepped frequency sweep sine signal are presented. In particular, the scattering of the water-filled aluminum spherical shell is compared with that of the air-filled one both theoretically and experimentally. The difference of the scattered signals are analyzed using the pseudo Wigner-Ville distribution in terms of average frequency, frequency distribution, and energy of the scattered signal. The result shows that all observed parameters increased when the aluminum sphere was water-filled, and it is well matched to the theoretical expectation.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.19-28
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• 2024

This paper proposes a method to improve the performance of ship identification through lofargram analysis of ship noise by applying the Hough Transform to a Convolutional Neural Network (CNN) model. When processing the signals received by a passive sonar, the time-frequency domain representation known as lofargram is generated. The machinery noise radiated by ships appears as tonal signals on the lofargram, and the class of the ship can be specified by analyzing it. However, analyzing lofargram is a specialized and time-consuming task performed by well-trained analysts. Additionally, the analysis for target identification is very challenging because the lofargram also displays various background noises due to the characteristics of the underwater environment. To address this issue, the Hough Transform is applied to the lofargram to add lines, thereby emphasizing the tonal signals. As a result of identification using CNN models on both the original lofargrams and the lofargrams with Hough transform, it is shown that the application of the Hough transform improves lofargram identification performance, as indicated by increased accuracy and macro F1 scores for three different CNN models.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.499-502
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• 1998

본 논문에서는 한 쌍의 수동소나를 이용하여 미지의 잠항물체의 존재 유무를 확인하고 각 센서에 도달하는 시간지연의 차를 평가하는 Detection과 Tracking 알고리즘을 연구한다. 이 과정에서 이동하는 표적의 속력에 의한 도플러효과를 보상하는 2차원 확률분포 함수를 적용함으로 보다 정확한 결과를 도출한다. 관측신호의 Cross-Correlation과 Bayesian Method를 이용하여 계산한 시간지연과 도플러효과 비의 이차원 Likelihood 함수로부터 사후확률 (Posterior Probability)을 구하여 발견 평가와 추적을 수행한다.

• 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).