• Title/Summary/Keyword: 표적소음

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Design and Implementation of Underwater Sound Analysis System for Target Identification (표적 식별을 위한 수중 음향 분석 시스템 설계 및 구현)

  • Yi, TaekJoon;Ryu, KeunHo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2004.05a
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    • pp.629-632
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    • 2004
  • 수중 표적을 식별하기 위해서는 표적이 방사하는 소음의 특징을 미리 알고 있어야 한다. 소음의 특징은 스펙트럼상의 상이한 주파수나 특징적 패턴을 형성하는데 수중에서 표적을 구별하는 주요 성분이다. 이 논문에서는 이런 표적의 고유 식별 정보를 모델링하고 구축하는 수중 음향 분석 시스템을 설계, 구현하였다. 이로써 표적관련 음파 특징 정보를 수치화하고 체계적으로 구축해 정밀분석의 토대를 마련하였다.

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Separation of passive sonar target signals using frequency domain independent component analysis (주파수영역 독립성분분석을 이용한 수동소나 표적신호 분리)

  • Lee, Hojae;Seo, Iksu;Bae, Keunsung
    • 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.

Tonal Signal Detection for Acoustic Targets using ASM Neural Network (ASM 신경망을 이용한 음향 표적의 토날 신호 탐지)

  • 이성은
    • 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.

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Detection of Signal Frequency Lines for Acoustic Target using Autoassociative Momory Neural Network (자동 연상 기억장치 신경망을 이용한 음향 표적의 신호 주파수선 탐지)

  • Lee, Sung-Eun;Hwang, Soo-Bok;Nam, Ki-Gon;Kim, Jae-Chang
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.5
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    • pp.118-124
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    • 1996
  • Signal frequency lines generated from the acoustic targets are of particular importance for target detection and classification in passive sonar systems. The underwater noise consists of a mixture of ambient noise and radiated noise of targets. Detction of exact signal frequency lines depends on signal detection threshold and variation of ambient noise. In this paper, a detection method of signal frequency lines for acoustic targets using autoassociative memory (ASM) neural network, which is not sensitive to variation of signal detection threshold and ambient noise, is proposed. It is confirmed by simulation and application of real acoustic targets that the proposed method shows good performance for detection of signal frequency lines.

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Own-ship noise cancelling method for towed line array sonars using a beam-formed reference signal (기준 빔 신호를 이용한 예인선배열 소나의 자함 소음 제거 기법)

  • Lee, Dan-Bi
    • The Journal of the Acoustical Society of Korea
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    • v.39 no.6
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    • pp.559-567
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    • 2020
  • This paper proposes a noise cancelling algorithm to remove own-ship noise for a towed array sonar. Extra beamforming is performed using partial channels of the acoustic array to get a reference beam signal robust to the noise bearing. Frequency domain Adaptive Noise Cancelling (ANC) is applied based on Normalized Least Mean Square (NLMS) algorithm using the reference beam. The bearing of own-ship noise is estimated from the coherence between the reference beam and input beam signals. Own-ship noise level is calculated using a beampattern of the noise with estimated steering angle, which prevents loss of a target signal by determining whether to update a filter so that removed signal level does not exceed the estimated noise level. Simulation results show the proposed algorithm maintains its performance when the own-ship gets out off its bearing 40 % more than the conventional algorithm's limit and detects the target even when the frequency of the target signal is same with the frequency of the own-ship signal.

The extraction method of unstable frequency line generated by underwater target using extended Kalman filter (확장 칼만필터를 이용한 수중 표적의 불안정 주파수선 추출 기법)

  • Lee, Sung-Eun;Hwang, Soo-Bok;Nam, Ki-Gon;Kim, Jae-Chang
    • 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.

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Wiener filtering-based ambient noise reduction technique for improved acoustic target detection of directional frequency analysis and recording sonobuoy (Directional frequency analysis and recording 소노부이의 표적 탐지 성능 향상을 위한 위너필터링 기반 주변 소음 제거 기법)

  • Hong, Jungpyo;Bae, Inyeong;Seok, Jongwon
    • The Journal of the Acoustical Society of Korea
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    • v.41 no.2
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    • pp.192-198
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    • 2022
  • As an effective weapon system for anti-submarine warfare, DIrectional Frequency Analysis and Recording (DIFAR) sonobuoy detects underwater targets via beamforming with three channels composed of an omni-direcitonal and two directional channels. However, ambient noise degrades the detection performance of DIFAR sonobouy in specific direction (0°, 90°, 180°, 270°). Thus, an ambient noise redcution technique is proposed for performance improvement of acoustic target detection of DIFAR sonobuoy. The proposed method is based on OTA (Order Truncate Average), which is widely used in sonar signal processing area, for ambient noise estimation and Wiener filtering, which is widely used in speech signal processing area, for noise reduction. For evaluation, we compare mean square errors of target bearing estmation results of conventional and proposed methods and we confirmed that the proposed method is effective under 0 dB signal-to-noise ratio.

An Algorithm for Submarine Passive Sonar Simulator (잠수함 수동소나 시뮬레이터 알고리즘)

  • Jung, Young-Cheol;Kim, Byoung-Uk;An, Sang-Kyum;Seong, Woo-Jae;Lee, Keun-Hwa;Hahn, Joo-Young
    • The Journal of the Acoustical Society of Korea
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    • v.32 no.6
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    • pp.472-483
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    • 2013
  • Actual maritime exercise for improving the capability of submarine sonar operator leads to a lot of cost and constraints. Sonar simulator maximizes the capability of sonar operator and training effect by solving these problems and simulating a realistic battlefield environment. In this study, a passive sonar simulator algorithm is suggested, where the simulator is divided into three modules: maneuvering module, noise source module, and sound propagation module. Maneuvering module is implemented in three-dimensional coordinate system and time interval is set as the rate of vessel changing course. Noise source module consists of target noise, ocean ambient noise, and self noise. Target noise is divided into modulated/unmodulated and narrowband/broadband signals as their frequency characteristics, and they are applied to ship radiated noise level depending on the vessel tonnage and velocity. Ocean ambient noise is simulated depending on the wind noise considering the waveguide effect and other ambient noise. Self noise is also simulated for flow noise and insertion loss of sonar-dome. The sound propagation module is based on ray propagation, where summation of amplitude, phase, and time delay for each eigen-ray is multiplied by target noise in the frequency domain. Finally, simulated results based on various scenarios are in good agreement with generated noise in the real ocean.

Target Signal Simulation in Synthetic Underwater Environment for Performance Analysis of Monostatic Active Sonar (수중합성환경에서 단상태 능동소나의 성능분석을 위한 표적신호 모의)

  • Kim, Sunhyo;You, Seung-Ki;Choi, Jee Woong;Kang, Donhyug;Park, Joung Soo;Lee, Dong Joon;Park, Kyeongju
    • The Journal of the Acoustical Society of Korea
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    • v.32 no.6
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    • pp.455-471
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    • 2013
  • Active sonar has been commonly used to detect targets existing in the shallow water. When a signal is transmitted and returned back from a target, it has been distorted by various properties of acoustic channel such as multipath arrivals, scattering from rough sea surface and ocean bottom, and refraction by sound speed structure, which makes target detection difficult. It is therefore necessary to consider these channel properties in the target signal simulation in operational performance system of active sonar. In this paper, a monostatic active sonar system is considered, and the target echo, reverberation, and ambient noise are individually simulated as a function of time, and finally summed to simulate a total received signal. A 3-dimensional highlight model, which can reflect the target features including the shape, position, and azimuthal and elevation angles, has been applied to each multipath pair between source and target to simulate the target echo signal. The results are finally compared to those obtained by the algorithm in which only direct path is considered in target signal simulation.

Target motion analysis algorithm using an acoustic propagation model in the ocean environment of South Korea (한국 해양환경에서 음파전달모델을 이용한 표적기동분석 알고리즘)

  • Seo, Ki Hoon
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.4
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    • pp.387-395
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    • 2019
  • TMA (Target Motion Analysis) in passive sonar is generally conducted with the bearing only or the bearing frequency. In order to conduct TMA fast and accurately, it is essential to estimate a initial target maneuver precisely. The accuracy of TMA can be improved by using SNR (Signal to Noise Ratio) information and acoustic propagation model additionally. This method assumes that the radiated noise level of the target is known, but the accuracy of TMA can be degraded due to a mismatch between the assumed radiated noise level and the actual radiated noise level. In this paper, TMA with the acoustic propagation model, bearing measurements, and SNR information is conducted in the ocean environment of South Korea (East Sea/ Yellow Sea/ South Sea). And the performance analysis of TMA for the mismatch in the radiated noise is presented.