• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.1
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• pp.51-58
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• 1997

In passive sonar, the frequency spectrum of a sound radiated by underwater moving targets is composed of a broadband nonuniform background noise and narrowband discrete tonals. To detect the tonals, the background noise is estimated and removed. Using the existing algorithms that estimate the background noise, a week tonals are not detected. Because a freuqency line that is formed by tonals which are being extracted continuously is a feture of the target, we are nessesory to efficiently detect the tonals that compose the frequncy line. In this paper, we propose an efficient neural network that can remove automatically the background and detect the even errl tonals, and we extract the frequency line feature on the spectrogram by the proposed algorithm. The experimental results for a ship's radiated sound show a better performance in comparison with the existing TPM algorithm.

• 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.

• 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.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.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.128-138
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• 2019

In this paper, we present fusion methods for two different lofargrams. Since the conventional method synthesizes the lofargrams using frequency spectrum, it has limited performance in fusion of tonal signals which have two-dimensional information of the time-frequency domain. Proposed algorithm uses a two-dimensional directional bilateral filter for preprocessing and fuses two lofargrams based on comparison of local anisotropy of the lofargrams. After noise is suppressed and tonals are sharpened, the local anisotropy can be used as a criterion to divide tonals and noise. The experiment results using simulated data and real data showed that the proposed algorithms result in similar or lower noise level of the fused lofargram than conventional algorithms and decrease tonal omission in fusion process.

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.47-53
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• 2000

In order to classify the underwater vehicles due to propeller propulsion, maximum likelihood classifier was developed. Propeller produces the cavitation and noise during its work. Cavitation-bubble makes the nonlinear medium in the water. The nonlinearity of cavitation leads to the generation of a complete spectrum of combination harmonics of the tonals of noise, and modulation of cavitation noise with propeller shaft-rates and blade-rates. The optimal estimator was derived mathematically and its capabilities were proven by simulation and real test.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.2
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• pp.20-34
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• 2003

The good sea-keeping capability of the SWATH(Small Waterplane Area Twin Hull) ship has been attractive for research or surveillance vessels. Especially, for the naval ships accomplishing the underwater acoustic missions, it is necessary to access and minimize the underwater radiated noise level generated by the ships. Therefore, acoustic signature management and control are very important topics for these vessels. Underwater radiation pattern in the low frequency range is dominated by the tonals from the vibration of onboard machinery. In this work, the radiated noise level generated by the propulsion machine in the submerged hull is predicted using the transfer function technique and the hull transfer function for the submerged hull is determined by analyzing the longitudinal/circumferential stiffened infinitely long cylindrical shell and considering the empirical database of the previous vessels. It is confirmed that the transfer function technique can give useful information for identifying the noise source and estimating its contribution to the total radiatied noise level.