• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.654-659
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• 2018

In this study, continuous long-term observation is implemented with an ocean radar. Ocean radar conducts remote observation (combined) with ground-based radars, which enable a series of simultaneous observations of an extensive range of the coast with high frequency. An ocean radar for continuous long-term observation is operated at Samcheok on the east coast of Korea. Samcheok experienced tsunami damage in recent years and is the location of a nuclear power plant. In order to examine the reliability of the ocean radar, a pressure-type wave gauge, ultrasonic wave gauge, and ocean buoy are installed for the purpose of data comparison and verification. The ocean radar used in this study is an array-type HF-RADAR named WERA (WavE RAdar). The analysis of the data obtained from continuous long-term observations showed that the radar observations were in agreement with more than 90% of the wave data collected within a 25 km range from the center of two sites. Less than 1% of the entire observation data was unmeasured by the time series analysis. As a result of comparing the radar data with the direct observations made by the wave gauge, it was inferred that the RMS deviation is less than 20cm and the correlation coefficient was in the range of 0.84 ~ 0.87. Moreover, supported by such observations, a comprehensive monitoring system is being developed to provide the public with real-time reports on waves and currents via the internet.

• Aerospace Engineering and Technology
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• v.13 no.1
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• pp.142-152
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• 2014

This paper analyzes the conjunction events of Korea satellites by year or kind of satellite using CSM, which is provided by JSpOC. If multiple CSM for single conjunction event are available, consistency analysis is performed using minimum range of CSM. And this paper presents the contact analysis results with space objects if there is a radar system in Korea. The effectiveness of Korea's radar system is analyzed by calculating the access time or frequency with space objects. Furthermore, we investigate the radar systems of other space agencies and find the specific parameter depending on the operating environment. Using this information, we define the requirements of radar system, which is appropriate the Korea.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.6
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• pp.810-820
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• 2014

Recently many studies of Radar systems mounted on ground vehicles for autonomous driving, SLAM (Simultaneous localization and mapping) and collision avoidance are reported. In near field, several hits per an object are generated after signal processing of Radar data. Hence, clustering is an essential technique to estimate their shapes and positions precisely. This paper proposes a method of grouping hits in range-doppler domains into clusters which represent each object, according to the pre-defined rules. The rules are based on the perceptual cues to separate hits by object. The morphological connectedness between hits and the characteristics of SNR distribution of hits are adopted as the perceptual cues for clustering. In various simulations for the performance assessment, the proposed method yielded more effective performance than other techniques.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.330-339
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• 2008

Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.39-46
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• 2019

In recently years, it has become important to detect underground objects of various marterials including metals, such as detecting the location of sink holes and pipe. For this reason, ground penetrating radar(GPR) technology is attracting attention in the field of underground detection. GPR irradiates the radar wave to find the position of the object buried underground and express the reflected wave from the object as image. However, it is not easy to interpret GPR images because the features reflected from various objects underground are similar to each other in GPR images. Therefore, in order to solve this problem, in this paper, to estimate the piping position in the GRP image according to the threshold value using the CNN (Convolutional Neural Network) model based on deep running, which is widely used in the field of image recognition, As a result of the experiment, it is proved that the pipe position is most reliably detected when the threshold value is 7 or 8.

• Journal of the Korean Geotechnical Society
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• v.37 no.9
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• pp.13-24
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• 2021

Recently, attempts have been made to detect fouling patterns in the ground using Ground Penetrating Radar (GPR) during the maintenance of gravel ballast railway tracks. However, dealing with GPR signal data obtained with a large amount of noise in a site where complex ground conditions are mixed, often depends on the experience of experts, and there are many difficulties in precise analysis. Therefore, in this study, a numerical modeling technique that can quantitatively simulate the GPR signal characteristics according to the degree of fouling of the gravel ballast material was proposed using python-based open-source code gprMax and RSA (Random sequential Absorption) algorithm. To confirm the accuracy of the simulation model, model tests were manufactured and the results were compared to each other. In addition, the identification of the fouling layer in the model test and analysis by various test conditions was evaluated and the results were analyzed.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.74-84
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• 2017

Since a soldier manages a hand-held landmine detector by hands, it is necessary to develop a system that can detect the target quickly and accurately. However, the hand-held landmine detector used in Korea has a problem that it can only detect the metal mines. Therefore, it is important to solve the problem and to develop a hand-held landmine detection system suitable for the Korean environment. In this paper, we propose a hand-held landmine detection system suitable for the Korean environment using ground penetrating radar. The proposed system uses depth compensation, matched filtering, and frequency shifting filtering for preprocessing. Then, in the detection step, the system detects the target using the edge ratio. In order to evaluate the proposed system, we buried landmines in sandy loam which is most of the soil in Korea and obtained a set of ground penetrating radar data by using a hand-held landmine detector. By using the obtained data, we carried out some experiments on the size and position of the patch and the shifting frequency to find the optimal parameter values and measured the detection performance using the optimized values. Experimental results show that the proposed preprocessing algorithms are suitable for detecting all landmines at low false alarm rate and the performance of the proposed system is superior to that of previous works.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.922-934
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• 2015

In this paper, The classification between precipitation echo(PRE) and non-precipitation echo(N-PRE) (including ground echo and clear echo) is carried out from weather radar data using neuro-fuzzy algorithm. In order to classify between PRE and N-PRE, Input variables are built up through characteristic analysis of radar data. First, the event classifier as the first classification step is designed to classify precipitation event and non-precipitation event using input variables of RBFNNs such as DZ, DZ of Frequency(DZ_FR), SDZ, SDZ of Frequency(SDZ_FR), VGZ, VGZ of Frequency(VGZ_FR). After the event classification, in the precipitation event including non-precipitation echo, the non-precipitation echo is completely removed by the echo classifier of the second classifier step that is built as Type-2 FCM based RBFNNs. Also, parameters of classification system are acquired for effective performance using PSO(Particle Swarm Optimization). The performance results of the proposed echo classifier are compared with CZ. In the sequel, the proposed model architectures which use event classifier as well as the echo classifier of Interval Type-2 FCM based RBFNN show the superiority of output performance when compared with the conventional echo classifier based on RBFNN.

• Journal of the Korean Geotechnical Society
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• v.34 no.11
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• pp.93-105
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• 2018

Precise investigation and interpretation of the ground subsidence risk factors needed to predict and evaluate the settlement problems of the surrounding ground due to the ground excavation. There are various geophysical exploration methods to investigate the ground subsidence risk factors. However, there are factors that influence the characteristics of the underground medium in these geophysical methods, and the actual soil contains complex factors affecting geophysical exploration. Therefore, it is necessary to analyze the effects on the geophysical methods based on the understanding of the geotechnical properties of soil. In this study, a test bed was constructed to consider various complicated factors in the complex ground and the ground behavior was analyzed by numerical analysis. In addition, we analyzed the limitations on investigating the ground subsidence risk factors through ground penetration radar (GPR) survey. As a result, ground subsidence of Open-cut Type Excavation is caused by various factors. Especially, in the case of soft ground condition, it was found that it was greatly influenced by the flow change of groundwater level. At the center frequency of GPR of 250 MHz, the attenuation of the electromagnetic wave is severely attenuated in the clay with high electrical conductivity, making it difficult to penetrate deeply into the ground (4 m below the surface). As the electromagnetic waves pass through the groundwater level below the groundwater, the attenuation of the electromagnetic waves becomes severe.

• Geomechanics and Engineering
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• v.16 no.3
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• pp.285-293
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• 2018

In densely populated urban areas with a large amount of infrastructure, ground subsidence events can result in massive casualties and economic losses. In South Korea, the incidence of ground subsidence in urban areas has increased in recent years and the number of underground cavities suspected of causing such events has significantly increased. Therefore, it is essential to develop techniques to prevent the occurrence of underground and ground subsidence. In this study, a field test, laboratory test, and numerical analysis were conducted to determine the optimal compaction degree of the upper support layer of any underground cavity below the level of sewer pipes in order to prevent such cavities from collapsing and leading to ground subsidence accidents. During the field test, an underground cavity was simulated using ice, and the generation of the cavity was confirmed using ground penetrating radar. The ground investigation was performed using a cone penetration test, and the compaction of the ground where ground subsidence occurred was evaluated with a laboratory test. The behaviour of the ground under various conditions was predicted using a numerical analysis based on the data obtained from the field test and previous studies. Based on these results, the optimal compaction degree of the ground required to prevent the underground cavity from causing ground subsidence was predicted and presented.