• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.65-73
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• 2002

Weather Radar have played an important role in both precipitation observation and hydrological operations over several countries and evaluated its efficient and necessities for the developed flood management and control. This paper describe the factors influencing the design the hydrological radar network in Korea and develop Hydrological Radar Network Simulation Model (HRNSM) based on GIS and UI system. Moreover, the methodologies for geographical and hydrological feasibility analysis for radar network were provided in detail manner.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.15-15
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• 2011

The radar observation system in Japan is operated by two governmental groups: Japan Meteorological Agency (JMA) and the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan. The JMA radar observation network is comprised of 20 C-band radars (with a wavelength of 5.6 cm), which cover most of the Japan Islands and observe rainfall intensity and distribution. And the MLIT's radar observation system is composed of 26 C-band radars throughout Japan. The observed radar echo from each radar unit is first modified, and then sent to the National Bureau of Synthesis Process within the MLIT. Through several steps for homogenizing observation accuracy, including distance and elevation correction, synthesized rainfall intensity maps for the entire nation of Japan are generated every 5 minutes. The MLIT has recently launched a new radar observation network system designed for flash flood observation and forecasting in small river basins within urban areas. It is called the X-band multi parameter radar network, and is distinguished by its dual polarimetric wave pulses of short length (3cm). Attenuation problems resulting from the short wave length of radar echo are strengthened by polarimetric wavelengths and very dense radar networks. Currently, the network is established within four areas. Each area is observed using 3-4 X-band radars with very fine resolution in spatial (250 m) and temporal (1 minute intervals). This study provides a series of utilization procedures for the new input data into a real-time forecasting system. First of all, the accuracy of the X-band radar observation was determined by comparing its results with the rainfall intensities as observed by ground gauge stations. It was also compared with conventional C-band radar observation. The rainfall information from the new radar network was then provided to a distributed hydrologic model to simulate river discharges. The simulated river discharges were evaluated again using the observed river discharge to estimate the applicability of the new observation network in the context of operations regarding flood forecasting. It was able to determine that the newly equipped X-band polarimetric radar network shows somewhat improved observation accuracy compared to conventional C-band radar observation. However, it has a tendency to underestimate the rainfall, and the accuracy is not always superior to that of the C-band radar. The accuracy evaluation of the X-band radar observation in this study was conducted using only limited rainfall events, and more cases should be examined for developing a broader understanding of the general behavior of the X-band radar and for improving observation accuracy.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.112-121
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• 2017

This study proposed the quantitative precipitation estimation method using overlapped area in radar network. For this purpose, the dense rain gauges and radar network are used. As a result, we found a reflectivity bias between two radar located in different area and developed the new quantitative precipitation estimation method using the bias. Estimated radar rainfall from this method showed the apt radar rainfall estimate than the other results from conventional method at overall rainfall field.

• Journal of Multimedia Information System
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• v.5 no.4
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• pp.245-256
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• 2018

This study estimated rainfall information more effectively by image signals through the information system of weather radar. Based on this, we suggest the way to estimate quantitative precipitation utilizing overlapped observation area of radars. We used the overlapped observation range of ground hyetometer observation network and radar observation network which are dense in our country. We chose the southern coast where precipitation entered from seaside is quite frequent and used Sungsan radar installed in Jeju island and Gudoksan radar installed in the southern coast area. We used the rainy season data generated in 2010 as the precipitation data. As a result, we found a reflectivity bias between two radar located in different area and developed the new quantitative precipitation estimation method using the bias. Estimated radar rainfall from this method showed the apt radar rainfall estimate than the other results from conventional method at overall rainfall field.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.223-229
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• 2006

This paper compares and analyzes the capabilities and application characteristic between the shipborne AIS and ARPA Radar. AIS base station and VTS Radar, give a brief introduction of the AIS base station network's building and application in China, and give a discussion on the information fusion and technology integrated of ATS and ARPA Radar, AIS base station network and VTS Radar.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.289-296
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• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.3
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• pp.307-322
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• 1992

For designing the radar integrated data network, we construct the network structure with a spatial hieratchy decomposition scheme. The RIDN can be decomposed into several subent classes, those of which are composed of the several group classes of radar sites, In a group class. The communication nodes of a radar site are modeled by the software modules formulated with the statistical attributes of discrete events. And we get the analysis over the network through the separately constructed infra group level models which were coded with the C language.From the result of the simulation. We could findthe fact that the data integration system;s performance approaches to the theordtically calculated value after being stable. And also we could get the packet processing status of a communication module’s inner processor which is difficult to oberve through the mathematical calculation tin the subnet model of the integrated data network.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.151-156
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• 2006

Accurate vessel traffic observation is indispensable to carry out vessel traffic management, design of vessel traffic route, planning of port construction, etc. In order to observe the vessel traffic accurately without many efforts such as the use of a ship or car equipped with special radar observation system and the preparation of observation staff, the authors have been developing completely automated remote radar/AIS network system covering the main traffic area in Tokyo Bay. The composite radar image observed at Yokosuka and Kawasaki radar stations with AIS information can be seen on web site of Internet. In addition to the development of radar/AIS observation system, the software to analyze observed vessel traffic flow has been developed. This software has various functions such as automatic tracking of ship's positions, automatic estimation of ship's size, automatic integration of radar image and AIS data, animation of ships' movements, extraction of dangerous ship encounters, etc. The configuration and functions of the developed remote radar/AIS network system are shown first in this paper. Then various functions of the software to analyze vessel traffic are introduced, and some analyzed results on the vessel traffic in Tokyo Bay are described demonstrating the effectiveness of the developed system.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.305-312
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• 2018

The quality of the radar and profiler network was estimated to forecast difficult meteorological situations. A network of UHF Doppler wind profilers and Doppler weather radars have been deployed all over the Korean Peninsular, with dense spatial resolution between instruments. The radar network allows to retrieve the three dimensional dynamics and to analyze the numerical model outputs at small and meso scales. This work has seldom been performed in any other place of the world, with such a high resolution. The wind field from radar network is a good agreement with the background wind fields based on the numerical modeling. This study will be helpful to forecast severe weathers as well as local meteorological phenomena.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.553-562
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• 2020

S-band, C-band and X-band radars are used for weather observation purposes. Since the Meteorological Administration, the Ministry of Environment, and Republic of Korea Air Force operate radars according to the purpose of observation by departments, the installation site and observation characteristics are different. From a meteorological point of view, blind observational areas in the low level with an elevation of less than 1 km around the mountainous terrain near Jirisan and Taebaeksan. Assuming a small radar installation, we simulated low-level observations. In order to monitor dangerous weather in North Korea, we analyzed the precipitation of North Korea and simulated a large radar network. Finally, a radar network for Korean Peninsula was proposed.