• Journal of Advanced Navigation Technology
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• v.8 no.1
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• pp.38-47
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• 2004

To achieve functions of doppler measurement, MTI(Moving Target Indicator), high-resolution, and others in radar system, all circuits of transmitter and receiver are to be performed in coherent system. In this paper, we use TWTA(Traveling Wave Tube Amplifier), STALO(Stable Local Oscillator) and COHO(Coherent Oscillator) to design of coherent radar transceiver, and calculates noise figure of designed receiver. Using radar equation calculated noise figure, maximum detecting range of each transmitting mode can be calculated.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.9-18
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• 2015

In recent years, the number of applications embedded in the various devices such as a smart phone is getting larger. Due to the frequent changes of states in the execution environment, various malfunctions may occur. In order to handle the issue, this paper suggests an approach to detecting method-level failures in the legacy software systems. We can determine if the software executes the abnormal behavior based on the behavior model. However, when we apply the context-sensitive behavior model to the method-level, several problems happen such as false alarms and monitoring overhead. To tackle those issues, we propose CIBFD (Context-Insensitive Behavior Model-based Failure Detection) method. Through the case studies, we compare CIBFD method with the existing method. In addition, we analyze the effectiveness of the method for each application domains.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.199-208
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• 2019

As the number of available satellites increases and technology advances, image information outputs are becoming increasingly diverse and a large amount of data is accumulating. In this study, we propose a change detection method for high-resolution satellite images that uses transfer learning and a deep learning network to overcome the limit caused by insufficient training data via the use of pre-trained information. The deep learning network used in this study comprises convolutional layers to extract the spatial and spectral information and convolutional long-short term memory layers to analyze the time series information. To use the learned information, the two initial convolutional layers of the change detection network are designed to use learned values from 40,000 patches of the ISPRS (International Society for Photogrammertry and Remote Sensing) dataset as initial values. In addition, 2D (2-Dimensional) and 3D (3-dimensional) kernels were used to find the optimized structure for the high-resolution satellite images. The experimental results for the KOMPSAT-3A (KOrean Multi-Purpose SATllite-3A) satellite images show that this change detection method can effectively extract changed/unchanged pixels but is less sensitive to changes due to shadow and relief displacements. In addition, the change detection accuracy of two sites was improved by using 3D kernels. This is because a 3D kernel can consider not only the spatial information but also the spectral information. This study indicates that we can effectively detect changes in high-resolution satellite images using the constructed image information and deep learning network. In future work, a pre-trained change detection network will be applied to newly obtained images to extend the scope of the application.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.12
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• pp.976-985
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• 2018

Modern radars such as the phase array radar can handle various tasks by generating a beam from a phased array antenna. Radar can be used for miscellaneous applications such as surveillance, tracking, missile guidance etc. Previous radar systems could handle only one task at a time. As such, multiple radars were required to perform simultaneous tasks. Multi-function radars can perform many tasks using only one radar system. However, the radar's resources are limited in this instance. To efficiently utilize time, it is necessary to properly schedule tasks in the radar's timeline. In this report, we investigate the efficiency of different scheduling tasks.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.11
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• pp.1141-1144
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• 2011

Range walk has been a major problem in achieving correct Doppler processing. This frequently occurs when range variation is severe just like in a bistatic radar or in high speed target scenario. This paper presents a range walk compensated range-Doppler processing algorithm applicable to the bistatic radar. In order for the compensation, a range-domain interpolation is applied for range compressed signal so that Doppler processing is performed along the evenly time-spaced range bins that contain target returns. Under a bistatic radar scenario, the proposed algorithm including a range domain pulse compression is mathematically described. Finally, the validity of the algorithm is demonstrated by simulation results showing the superiority of a SCDP(Squint Cross-range Doppler Processing) over an uncompensated Doppler processing.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.145-150
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• 2008

This paper suggests an applicable study on Helix TWT of Slow-Wave Structure for Surveillance RADAR. In order to improve Slow-Wave Structure performance and analysis, we design and realizer a Helix TWTA using a HFSS Code and LMSuite Code, Through the cutting and simulation of Helix TWTA, this parameter satisfies the design specifications, Therefore, this specifics is very useful and can be used to develop the similar equipments.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.69-82
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• 2020

In many technologies, artificial intelligence (AI) is becoming an important topic for areas based on the field of big data. However, applied AI cases and the research status of radio wave technology are not widely known to the public. The spread of AI to other areas is being followed by radio wave technologies, and much effort is being taken to evolve it into intelligent radio wave technologies in the future. This paper presents the recent areas of interest in radio wave technology, such as spectral sharing, illegal spectrum monitoring, radar detection, radio wave medical imaging, and channel modeling; examines the requirements for applying AI; and describes the applied cases, research trends, and standardization efforts that apply AI technology to them. On this basis, we will discuss the prospects of AI application to the expected radio wave technology of the future.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.3
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• pp.214-224
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• 2018

Continuous space development increases the occurrence probability of space hazards such as collapse of a satellite and collision between a satellite and space debris. In Korea, a space surveillance network with optical system has been developed; however, the radar technology for an independent space surveillance needs to be secured. Herein, an L-band phased array radar system for the detection and tracking of space objects is proposed to provide a number of services including collision avoidance and the prediction of re-entry events. With the mission analysis of space surveillance and the case analysis of foreign advanced radar systems, the radar parameters are defined and designed. The proposed radar system is able to detect a debris having a diameter of 10 cm at a maximum distance of 1,576 km. In addition, we confirmed the possibility of using the space surveillance mission for domestic satellites through the analysis of the detection area.

• Economic and Environmental Geology
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• v.37 no.2
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• pp.185-193
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• 2004

A physical model experiment was conducted using a sand and gravel-filled tank model, to investigate the influence on the GPR response of LNAPL vapor phase effects in the unsaturated zone and of residual phase of LNAPL trapped in the saturated zone. Background measurements of GPR were made with only water in the tank using a fluctuating water table model. Gasoline was, then, injected into the bottom of the model tank to simulate a subsurface discharge from a leaking pipe or tank at depth, obtaining GPR data with rising and lowering of water table. Results from the experiment show the GPR sensitivity to the changes in the moisture content in the vadose zone and its effectiveness for monitoring minor fluctuation of the water table. The results also demonstrate a potential of GPR for monitoring possible vapor phase effects of volatile hydrocarbons in the vadose zone as a function of time, and for detecting the effects of residual phase of hydrocarbons in the water saturated system. In addition, the results provide the basis for a strategy that has the potential to successfully detect and delineate residual LNAPL contamination in the water-saturated system at field sites where the conditions are similar to those simulated in the physcial models described herein.

• Geophysics and Geophysical Exploration
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• v.20 no.2
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• pp.61-71
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• 2017

Recently, ground-penetrating radar (GPR) surveys have been actively carried out for precise subsurface void investigation because of the rapid increase of subsidence in urban areas. However, since the interpretation of GPR data was conducted based on the interpreter's subjective decision after applying only the basic data processing, it can result in reliability problems. In this research, to solve these problems, we analyzed the difference between the events generated from subsurface voids and those of strong diffraction sources such as the buried pipeline by applying the edge detection technique, which is one of image processing technologies. For the analysis, we applied the image processing technology to the GRP field data containing events generated from the cavity or buried pipeline. As a result, the main events by the subsurface void or diffraction source were effectively separated using the edge detection technique. In addition, since subsurface voids associated with the subsidence has a relatively wide scale, it is recorded as a gentle slope event unlike the event caused by the strong diffraction source recorded with a sharp slope. Therefore, the directional analysis of amplitude variation in the image enabled us to effectively separate the events by the subsurface void from those by the diffraction source. Interpretation based on these kinds of objective analysis can improve the reliability. Moreover, if suggested techniques are verified to various GPR field data sets, these approaches can contribute to semiautomatic interpretation of large amount of GPR data.