• Title/Summary/Keyword: 토널 추출

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Tonal Extraction Method for Underwater Acoustic Signal Using a Double-Feedback Neural Network (이중 회귀 신경 회로망을 이용한 수중 음향 신호의 토널 추출 기법)

  • Lim, Tae-Gyun;Lee, Sang-Hak
    • 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.

A DEMON Processing Robust to Interference of Tonals (토널 신호 간섭에 강인한 데몬 처리 기법)

  • Kim, Jin-Seok;Hwang, Soo-Bok;Lee, Chul-Mok
    • The Journal of the Acoustical Society of Korea
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    • v.31 no.6
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    • pp.384-390
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    • 2012
  • Passive sonars employ DEMON(Detection of Envelope Modulation on Noise) processing to extract propeller information from the radiated noise of underwater targets. However, the conventional DEMON processing suffers from the interference of tonal signals because it extracts propeller signals and some types of tonal signals as well. If there are some tonals in the frequency band for DEMON processing, the conventional DEMON processing may additionally extract frequency informations originated from the interaction between different tonals. In this paper, we propose a modified DEMON processing, which can eliminate the interference of the tonals. The proposed algorithm removes tonals in DEMON processing band before demodulation processing, hence results the robustness to the interference of the tonals. Some numerical simulations demonstrate the improved performance of the proposed algorithm against the conventional algorithm.

A Study on the Automatic Detection and Extraction of Narrowband Multiple Frequency Lines (협대역 다중 주파수선의 자동 탐지 및 추출 기법 연구)

  • 이성은;황수복
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.8
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    • pp.78-83
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    • 2000
  • Passive sonar system is designed to classify the underwater targets by analyzing and comparing the various acoustic characteristics such as signal strength, bandwidth, number of tonals and relationship of tonals from the extracted tonals and frequency lines. First of all the precise detection and extraction of signal frequency lines is of particular importance for enhancing the reliability of target classification. But, the narrowband frequency lines which are the line formed in spectrogram by a tonal of constant frequency in each frame can be detected weakly or discontinuously because of the variation of signal strength and transmission loss in the sea. Also, it is very difficult to detect and extract precisely the signal frequency lines by the complexity of impulsive ambient noise and signal components. In this paper, the automatic detection and extraction method that can detect and extract the signal components of frequency tines precisely are proposed. The proposed method can be applied under the bad conditions with weak signal strength and high ambient noise. It is confirmed by the simulation using real underwater target data.

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A Blind Audio Watermarking using the Tonal Characteristic (토널 특성을 이용한 브라인드 오디오 워터마킹)

  • 이희숙;이우선
    • Journal of Korea Multimedia Society
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    • v.6 no.5
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    • pp.816-823
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    • 2003
  • In this paper, we propose a blind audio watermarking using the tonal characteristic. First, we explain the perceptional effect of tonal on the existed researches and shout the experimental result that tonal characteristic is more stable than other characteristics used in previous watermarking studies against several signal processing. On the base of the result, we propose the blind audio watermarking using the relation among the signals on the frequency domain which compose a tonal masker. To evaluate the sound quality of our watermarked audios, we used the SDG(Subjective Diff-Grades) and got the average SDG 0.27. This result says the watermarking using the perceptional effect of tonal is available from the viewpoint of non-perception. And we detected the watermark hits from the watermarked audios which were changed by several signal processing and the detection ratios with exception of the time shift processing were over 98%. About the time shift processing, we applied the new method that searched the most proper position on the time domain and then detected the watermark bits by the ratio of 90%.

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A Study on the Automatic Detection and Extraction of Narrowband Multiple Frequency Lines (협대역 다중신호 주파수선의 자동 탐지 및 추출기법 연구)

  • Lee Sung-Eun;Hwang Soo-Bok
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.181-184
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    • 2000
  • 수중신호의 스펙트로그램상에 형성되는 신호 주파수선은 토널의 신호 세기와 바다 자체의 전달 특성 등으로 인하여 미약하게 탐지되거나 불규칙하게 끊어져서 불연속하게 되며 또한 임펄스성의 주변잡음 성분과 혼재하여 어느 토널이 연속적으로 탐지되는지가 모호하게 되는 경우가 많고 정밀하게 신호 성분만을 탐지, 추출하기가 어렵다. 따라서 본 논문에서는 신호 세기가 미약한 경우나 높은 주변잡음이 복합되어 있는 경우에도 정밀하게 신호 성분만을 탐 지, 추출할 수 있는 협대역 다중 주파수선의 자동 탐지 및 추출을 위한 기법을 제안한다. 제안된 알고리즘에 실제 수중표적 신호를 적용하여 제안된 알고리즘이 매우 유용함을 보인다.

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Classification and Tracking of Unknown Multiple Underwater Moving Objects Using Neural Networks (신경망에 의한 미지의 다중 수중 이동물체의 판별 및 추적)

  • 하석운
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.2
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    • pp.389-396
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    • 1999
  • In this paper, we propose a multiple underwater object classification and tracking algorithm using the narrowband tonal and frequency line features extracted from the frequency spectrum of the acoustic signal. The general algorithm using the wideband and narrowband energy has a high tracking error when objects are close and cross each other. But the proposed algorithm shows a good tracking performance for the simulation scenarios generated by the real acoustic data.

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