• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.215-220
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• 2005

In order to apply to land mine detection effectively, GPR using an optical electric field sensor as a receiver has been developed. The optical electric field sensor is very small and uses optical fiber instead of metallic coaxial cable. With the combination of these advantages and the bistatic radar system, it can be possible for an operator to measure quite flexible and safely. The sensor has been tested in stepped frequency radar system with frequency which consists of a vector network analyzer, a fixed double ridged horn antenna as transmitter. For considering effectiveness in real field, we applied impulse radar system, which consist of a digital oscilloscope and a impulse generator to produce the impulse. Detection of a PMN2 mine model was carried out by the impulse radar system at a sand pit. The PMN2 were detected clearly with sufficiently high resolution, the target contrast was almost the same while the scanning time decreased down to 1/100.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.7-14
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• 2006

The radar relationship was estimated for the selected rainfall event at Yeongchun station within Chungjudam basin where the discharge record was the range of from 1,000 CMS to 9,000 CMS. By calibrating the rainfall coefficient parameter estimated by radar relationship in small hydrology basin, rainfall with the topography properties was calculated. Three different rainfall estimation methods were compared:(1) radar relationship method (2) Thiessen method (3) Isohyetal method (4) Inverse distance method. Basin model was built by applying HEC-GeoHMS which uses digital elevation model to extract hydrological characteristic and generate river network. The proposed basin model was used as an input to HEC-HMS to build a runoff model. The runoff estimation model applying radar data showed the good result. It is proposed that the radar data would produce more rapid and accurate runoff forecasting especially in the case of the partially concentrated rainfall due to the atmospheric change. The proposed radar relationship could efficiently estimate the rainfall on the study area(Chungjudam basin).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1785-1796
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• 1993

Thanks to the data processing facilities of modern digital computers, the performances of radar has been promoted greatly as one of the main components of command and control systems along with the computer communications. In this study, radar data integrating and processing systems were designed for the data processing of various information from many kinds of radar in a single data processing system. The performance of the data integrating system was analyzed by applying queueing theory. A radar data integrating network was designed for synchronous relational operations among the information processing systems and the transmission characteristics were also analysed by specific models for each system. The designed data integrating systems can be divided into a simplex type and a distributed multiplex type.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.99-106
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• 2015

In this study, we propose Radial basis function Neural Network(RBFNN) using Recursive Weighted Least Square Estimation(RWLSE) to effectively deal with big data class meteorological radar data. In the condition part of the RBFNN, Fuzzy C-Means(FCM) clustering is used to obtain fitness values taking into account characteristics of input data, and connection weights are defined as linear polynomial function in the conclusion part. The coefficients of the polynomial function are estimated by using RWLSE in order to cope with big data. As recursive learning technique, RWLSE which is based on WLSE is carried out to efficiently process big data. This study is experimented with both widely used some Machine Learning (ML) dataset and big data obtained from meteorological radar to evaluate the performance of the proposed classifier. The meteorological radar data as big data consists of precipitation echo and non-precipitation echo, and the proposed classifier is used to efficiently classify these echoes.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.1 s.116
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• pp.31-36
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• 2007

In the RFID system, one of the important criteria of tag antenna performance is the detection distance. The most important factor determining the detection distance of the tag antenna is the Radar Cross Sections(RCS). In this paper, we propose a method to simply measure the RCS of the RFID tag antenna using two reader antennas(Tx and Rx) and a network analyzer. We estimate RCS' from the RCS equation based on the measured $S_{21}$ using the network analyzer. We compare the measured $S_{21}$ values with the calculated $S_{21}$ values and the simulated $S_{21}$ values using EM simulator. The used tag antennas are two kinds of dipole-type, metal-type, and an inductively-coupled type ones. In case of the dipole type, the measured, simulated and calculated values of the RCS are almost the same. In case of other types, we obtain the measured RCS values with a difference of about 3 dB.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.12
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• pp.1100-1107
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• 2015

In this paper, we propose an algorithm to identify Wobble PRI and Sinusoidal PRI among Radar pulses. We applied not only the DTOA(Difference Time Of Arrival) concept of radar pulse signals incoming to antennas but also a rising and falling cub characteristic of those PRIs. After making a program by such algorithm, we input each 40 data to Wobble PRI's and Sinusoidal PRI's identification programs and in result, those programs fully processed the data the according to expectations. In the future, those programs can be applied to the ESM, ELINT system.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.562-568
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• 2014

There exist precipitation echo and non-precipitation echo in the meteorological radar. It is difficult to effectively issue the right weather forecast because of a difficulty in determining these ambiguous point. In this study, Data is extracted from UF data of meteorological radar used. Input and output data for designing two classifier were built up through the analysis of the characteristics of precipitation and non-precipitation. Selected input variables are considered for better performance and echo classifier is designed using fuzzy relation-based nueral network. Comparative studies on the performance of echo classifier are carried out by considering both echo judgement module 1 and module 2.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.12
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• pp.1460-1466
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• 2010

In this paper, we analyzed the performance of radar target classification using the monostatic and bistatic radar cross section(RCS) for four different wire targets. Short time Fourier transform(STFT) and continuous wavelet transform (CWT) were used for feature extraction from the monostatic RCS and the bistatic RCS of each target, and a multi-layered perceptron(MLP) neural network was used as a classifier. Results show that CWT yields better performance than STFT for both the monostatic RCS and the bistatic RCS. And, when STFT was used, the performance of the bistatic RCS was slightly better than that of the monostatic RCS. However, when CWT was used, the performance of the monostatic RCS was slightly better than that of the bistatic RCS. Resultingly, it is proven that bistatic RCS is a good cadndidate for application to radar target classification in combination with a monostatic RCS.

• JSTS:Journal of Semiconductor Technology and Science
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• v.8 no.2
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• pp.139-142
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• 2008

An X-band MMIC power amplifier for radar application is developed using $0.25-{\mu}m$ gate length GaAs pHEMT technology. A bus-bar power combiner at output stage is used to minimize the combiner size and to simplify bias network. The fabricated power amplifier shows 38.75 dBm (7.5 Watt) Psat at 10 GHz. The chip size is $3.5\;mm{\times}3.9\;mm$.