• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.418-424
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• 2018

Detection and classification of underwater targets is an important issue for both military and non-military purposes. Recently, many performance improvements are being reported in the field of pattern recognition with the development of deep learning technology. Among the results, DBN showed good performance when used for pre-training of DNN. In this paper, DBN was used for the classification of underwater targets using active sonar, and the results are compared with that of the conventional BPNN. We synthesized active sonar target signals using 3-dimensional highlight model. Then, features were extracted based on FrFT. In the single aspect based experiment, the classification result using DBN was improved about 3.83% compared with the BPNN. In the case of multi-aspect based experiment, a performance of 95% or more is obtained when the number of observation sequence exceeds three.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.231-238
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• 2022

Mine detection has been mainly studied with images of the forward-looking sonar. Forward-looking sonar assumes the propagation path of the sound wave as a straight path, creating the surrounding images. This might lead to errors in the detection by ignoring the refraction of the sound wave. In this study, we propose a mine localization method that can robustly identify the location of mines in an underwater environment by considering the refraction of sound waves. We propose a method of estimating the elevation angle of arrival of the target echo signal in a single receiver, and estimate the mine location by applying the estimated elevation angle of arrival to ray tracing. As a result of simulation, the method proposed in this paper was more effective in estimating the mine localization than the existing method that assumed the propagation path as a straight line.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.221-228
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• 2020

A sonobuoy is dropped onto the surface of water to estimate the bearing of an underwater target. A Directional Frequency Analysis and Recording (DIFAR) sonobuoy has an error in the specific angular section due to the method of estimating bearing and noise, which causes an error in target localization using multiple sonobuoys. In addition, the position of the sonobuoy continues to move, but since a sonobuoy with a GPS is intermittently arranged, it is difficult to estimate the exact position of the sonobuoy. This also causes target localization performance degradation. In this paper, we propose a technique to improve the target localization performance by compensating for bearing errors using characteristics of the DIFAR sonobuoy and multiple-sonobuoy position errors based on the intermittently arranged active sonobuoy with a GPS.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.19 no.5
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• pp.84-90
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• 2000

The bearing detection of radiated target noise is very important at underwater acoustic measurement and passive detection. It differs the arrival tines of received signal at each sensor. Therefore, the bearing can be obtained from the time delay. This paper proposes a new algorithm using the RLSL adaptive filter for TDE. The proposed method is particularly attractive when there is a limitation of priori information about the received signal spectra and when the delay is subject to variation. As the simulation results, it is shown that the proposed algorithm has better convergence characteristics and TDE speed, and so that the usefulness of proposed algorithm is confirmed.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.1
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• pp.40-46
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• 2018

In order to successfully detect and identify underwater targets located on the seabed, unmanned surface vehicles (USVs) typically acquire acoustic signals with a side-scan sonar device and reconstruct information about the target from the processed images. As the quality of the side-scan sonar images acquired by USVs depends on the environment and operating parameters, using modeling and simulation techniques to design side-scan sonar devices can help optimize the reconstruction of the sonar images. In this work, we study a side-scan sonar design for use in USVs, that takes the movement of the platform into account. First, we constructed a simulated seabed environment with underwater targets, and specified the maneuvering conditions and sonar systems. We then generated the acoustic signals from the simulated environment using the sonar equation. Finally, we successfully imaged the simulated seabed environment using simple signal processing. Our results can be used to derive USV side-scan sonar design parameters, predict the resulting sonar images in various conditions, and as a basis for determining the optimal sonar parameters of the 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2227-2232
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• 2013

To obtain the system requirement specification in the beginning of the precision guidance system development, the effectiveness and reliability analysis for the system are necessary. The main purpose of this research is to obtain the system requirement specification for the high speed unmanned underwater vehicles by carrying out the effectiveness analysis using the modeling and simulation scheme. The effectiveness is position error for target position. Reaching accuracy is expected to be affected by the navigation sensor parameter. Assume that the navigation sensors that is consist of inertial navigation system(INS) and doppler velocity log(DVL) is the parameter. To analyze the effectiveness of each parameter, Monte-Carlo numerical simulation is performed in this research. The effectiveness analysis is carried out using circular error probability(CEP) and variance analyze scheme. Considering the cost function, the specification of the navigation sensor is provided. The cost function is consist of the INS and DVL specification and the price of those sensors.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.774-780
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• 2009

This paper proposes a transmitted power saving method for underwater acoustic sensors considering the acoustic wave propagation characteristic that propagation loss increases more rapidly in higher frequency band. In the proposed scheme, sensor nodes are divided into a few groups based on the distance between sink node and the sensor node, and each group uses its own frequency band. The node group with longer distance uses lower frequency and the node group with shorter distance uses higher frequency. By means of such a distance-dependent frequency allocation, all sensor nodes are able to maintain a certain target signal-to-noise ratio (SNR), but also save transmitted power. In addition, the optimum size of node group is obtained, and also a frequency allocation algorithm is proposed accordingly. Numerical results show that the proposed scheme saves transmitted power by more 10 dB comparing non-grouping methods.