• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.401-407
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• 2021

The continuous active sonar technology is effective for detecting and tracking targets because of short target revisiting rate. Generalized Sinusoidal Frequency Modulation (GSFM) pulses suitable for continuous active sonar systems are known to be capable of obtaining high time-bandwidth product while maintaining the orthogonality between pulses. However, it is unknown how to calculate an appropriate length of time to correlate received GSFM pulses in the presence of a target with acceleration. In this paper, we propose a method to calculate the appropriate time length based on the correlation when matching the received signal in the continuous active sonar system using GSFM pulse. The proposed method calculates the correlation according to the acceleration of the target and calculates the signal processing length according to the correlation. It is shown that stable detection performance can be obtained when the signal processing length calculated by the proposed method through the level of the sidelobe is applied.

• The Journal of the Acoustical Society of Korea
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• v.38 no.4
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• pp.415-426
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• 2019

In this paper, we discussed automatic target tracking algorithms for diver detection sonar that observes penetration forces of coastal military installations and major infrastructures. First of all, we analyzed sea trial data in diver detection sonar and composed automatic target tracking algorithms based on track existence probability as track quality measure in clutter environment. In particular, these are presented track management algorithms which include track initiation, confirmation, termination, merging and target tracking algorithms which include single target tracking IPDAF (Integrated Probabilistic Data Association Filter) and multitarget tracking LMIPDAF (Linear Multi-target Integrated Probabilistic Data Association Filter). And we analyzed performances of automatic target tracking algorithms using sea trial data and monte carlo simulation data.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.26 no.3
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• pp.123-128
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• 2007

This Paper Presents new transient signal classification algorithms for underwater transient signals. In general. the ambient noise has small spectral deviation and energy variation. while a transient signal has large fluctuation. Hence to detect the transient signal, we use the spectral deviation and power variation. To classify the detected transient signal. the feature Parameters are obtained by using the Wigner-Ville distribution based eigenvalue decomposition. The correlation is then calculated between the feature vector of the detected signal and all the feature vectors of the reference templates frame-by-frame basis, and the detected transient signal is classified by the frame mapping rate among the class database.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1259-1268
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• 2015

The sonic layer depth (SLD) variability is important for understanding the acoustic properties of the upper ocean that influence acoustic communications, acoustic tomography, and naval operations related to searching and detecting marine underwater vessels. Generally, the SLD is the acoustical equivalent of the mixed layer depth (MLD), although they are defined differently. In this study the SLD was compared with the MLD over the annual cycle in the East Sea using an available set of temperature-salinity observation profiles. For the comparison, various definitions and methods of the MLD had applied. As a result, the SLD in the East Sea is slight similar to the curvature method applied MLD, but the other MLD have severe differences with the SLD. Futhermore, a parabolic equation transmission model is used to evaluate the cutoff frequency trapped in surface duct. It follow that there is an optimum frequency for propagation at which the loss of sound is minimum.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.209-217
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• 2011

This study incorporate hydroacoustic sampling for bathymetry and sediment survey in Won Cheon reservoir, Suwon city, Korea. Bathymetric and sedimentation surveys were conducted using a echo sounder system and subbottom profiler in the reservoirs. Data were collected using echo sounder systems and subbottom profiler linked to a GPS, to maximize data accuracy and vessel use, and geo-referenced using a DGPS enabling the acoustic data to be used in a GIS. Echo sounder and subbottom survey data were merged within geographic information system(GIS) software to provide detailed visualization and analyses of current depths, pre-impoundment topography, distribution, thickness, and volume estimates of lacustrine sediment, and water storage capacity. These data and analyses are, necessary for development of long term management plans for these reservoirs and their watersheds.

• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.158-164
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• 2017

Typical hydrophones in line array sensors for early detection of covert underwater targets can measure only sound-pressure-magnitude with the limitation of being unable to identify the direction of an incoming wave. In this study, a thickness shear mode vibrator was proposed as the main component of an inertia type vector hydrophone to measure both magnitude and direction of acoustic signals from targets. The equation to analyze the output voltage of the vibrator to an external force was derived, and the validity of the equation was verified through finite element analysis of a PMN-PT single crystal vibrator. The analysis results from this study will be utilized in the future for the design of inertia type vector hydrophones made of thickness shear vibrators.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1253-1258
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• 2013

This Paper deals with detection and defense methods for underwater weapons because there are so many dangers of underwater weapons not only in the war period but also in the peace time. Underwater mines are the representative strategic arms. The sensors and target detection methods, threat elimination method of mines included in this paper. Among the various sensors of mine, we use the magnetometor for target detection method in the simulation and execute the analysis of magnetic field of detected target ships. It will be also provided that effectiveness of target detection, sweeping method of mine, tactics of mine planning and mine sweeping and so on.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.225-233
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• 2024

Active sonar transmits sound waves to detect covertly maneuvering underwater objects and detects the signals reflected back from the target. However, in addition to the target's echo, the active sonar's received signal is mixed with seafloor, sea surface reverberation, biological noise, and other noise, making target recognition difficult. Conventional techniques for detecting signals above a threshold not only cause false detections or miss targets depending on the set threshold, but also have the problem of having to set an appropriate threshold for various underwater environments. To overcome this, research has been conducted on automatic calculation of threshold values through techniques such as Constant False Alarm Rate (CFAR) and application of advanced tracking filters and association techniques, but there are limitations in environments where a significant number of detections occur. As deep learning technology has recently developed, efforts have been made to apply it in the field of underwater target detection, but it is very difficult to acquire active sonar data for discriminator learning, so not only is the data rare, but there are only a very small number of targets and a relatively large number of non-targets. There are difficulties due to the imbalance of data. In this paper, the image of the energy distribution of the detection signal is used, and a classifier is learned in a way that takes into account the imbalance of the data to distinguish between targets and non-targets and added to the existing technique. Through the proposed technique, target misclassification was minimized and non-targets were eliminated, making target recognition easier for active sonar operators. And the effectiveness of the proposed technique was verified through sea experiment data obtained in the East Sea.

• 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.