• 대한원격탐사학회지
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• 제8권2호
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• pp.79-91
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• 1992

최근 지구궤도상 영상레이다 시스템의발전과 더불어 여러 응용분야에서 레이다 원격탐사 자료를 이용하려는 관심이 높아지고 있다. 본 연구는 우주상공에서 얻은 레이다영상자료로부터 얻은 레이다반사치와 산림의 특성과의 상관관계를 밝히고자 하였다. 미국 플로리다 북부 산림지 대의 연구지역을 대상으로 하여 1984년 10월 우주왕복선 비행에서 Shuttle Imaging Radar B(SIR-B) 자료를 얻었다. 여러 종류의 참고자료(임분 조사자료, 임상도, 항공사진, Landsat Thematic Mapper 자료)를 이용하여 약 400여개 의 표본임분을 선정하였다. 각 임분의 물리적 특 성(평균수고, 흉고직경, 수간밀도, 생체량, 하층식생량)과 그에 따른 레이다반사치와를 비교하였고 그들간에 통계학적으로 유의성이 있는 상관관계를 볼 수 있었다. 또한, 동일한 임분특성에서도 레 이다반사치가 세 개의 주사각도별로 다르게 나타나고 있었다. 끝으로 최근 우리에게 이용가능한 인공위성 레이다영상자료의 종류와 특성 및 전망 등을 살펴보았다.

• 한국멀티미디어학회논문지
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• 제18권4호
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• pp.473-482
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• 2015

Doppler weather radar is an important tool for meteorological research. Through several decades of development, Doppler weather radar has enormous progress in understanding, detection and warning of meso and micro scale weather system. It makes a significant contribution to weather forecast and weather disaster warning. But the large amount of data process limits the application of Doppler weather radar. This paper proposed for fast weather radar data processing based on CUDA. CDUA is a powerful platform for highly parallel programming developed by NVIDIA. Through running plenty of threads, radar data can be calculated at same time. In experiment, CUDA parallel program can significantly improve weather data processing time.

• 한국멀티미디어학회논문지
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• 제20권12호
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• pp.1874-1889
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• 2017

The paper aims to analyze structure of I/Q data observed from radar and reliably estimate rainfall through quality control of I/Q data that can quantify uncertainty of I/Q data occurring due to resultant errors. Radar rainfall data have strong uncertainty due to various factors influencing quality. In order to reduce this uncertainty, previously enumerated errors in quality need to be eliminated. However, errors cannot be completely eliminated in some cases as seen in random errors, so uncertainty is necessarily involved in radar rainfall data. Multi-Lag Method, one of I/Q data quality control methods, was applied to estimate precipitation with regard to I/Q data of rainfall radar in Mt. Sobaek.

• 한국산업정보학회논문지
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• 제5권3호
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• pp.44-50
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• 2000

본 논문에서는 이동식 기상 레이더를 효율적으로 운용하기 위한 자료 처리시스템에 관하여 논하였다. 이동식 기상 레이더는 특별한 목적을 위해 관찰 지역을 이동할 수 있다는 점에서 매우 유용한 장비이다. 무엇보다도 이 장비의 효용성을 높이기 위해서는 레이더 시스템과 기상 센터간의 원격지 데이터 전송이 이루어져야 한다. 또한 전송된 원시 데이터를 가지고 대기의 특성을 분석하고 사용자가 원하는 형태로 저장하고 표출할 수 있어야 한다. 이 논문에서는 이런 목적을 이루기 위해 레이더 시스템과 원격지 기상센터간에 데이터를 주고받기 위하여 무선 LAN 방식을 사용하였으며 또한 전송된 데이터를 이용하여 이동식 레이더에 효율적인 영상 표출 시스템을 개발하였다. 이 시스템은 실시간 에코 추적과 그래픽 및 동영상 검색에도 사용될 수 있다.

• 한국수자원학회논문집
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• 제52권1호
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• pp.21-33
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• 2019

본 연구에서는 비슬산 이중편파 Radar 자료와, GPM 위성자료 및 21개 (Korea Meteorological Administration, KMA) 지상강우자료를 활용하여 분포형 강우-유출 모형(KIneMatic wave STOrm Runoff Model2, KIMSTORM2)을 이용해 남강댐 유역($2,293km^2$)을 대상으로 유출해석을 수행하였다. 모형의 유출 해석은 2016년 10월 5일 02:00~09:00 총 8시간 동안 최대강우강도 33 mm/hr, 유역평균 총 강우량 82 mm이 발생한 태풍 차바(CHABA)를 대상으로 하였으며, Radar 및 GPM 자료와 조건부합성(Conditional Merging, CM) 기법을 적용한 Radar (CM-corrected Radar) 및 GPM (CM-corrected GPM) 자료를 각각 활용하여 결과를 비교하였다. 이 때, 공간 강우자료에 유출 검보정은 남강댐 유역 내 3개의 수위관측 지점(산청, 창촌, 남강댐)을 대상으로 실시하였으며, 모형의 매개변수 초기토양수분함량, 지표와 하천의 Manning 조도계수를 이용하여 검보정하였다. 유출 결과는 결정계수(Determination coefficient, $R^2$), Nash-Sutcliffe의 모형효율계수(NSE) 및 유출용적지수(Volume Conservation Index, VCI)를 산정하였다. 그 결과 CM-corrected Radar, GPM 자료가 평균 $R^2$는 0.96, NSE의 경우 0.96, 유출용적지수(VCI)는 1.03으로 가장 우수한 결과를 나타내었다. 최종적으로 CM 기법을 이용한 보정된 공간분포자료는 기존의 자료에 비해 시공간적으로 정확한 홍수 예측에 사용 될 것으로 판단된다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.522-522
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• 2015

In this study, the effect of threshold applied to the radar rain rate on the comparison of the radar and rain gauge rain rate was theoretically examined. The result derived was also evaluated theoretically, using the Bernoulli random field, and empirically, using Mt. Kwanak weather radar data. The results are summarized as follows. (1) In the application to the Bernoulli random field, it was found that the comparison of the radar and rain gauge rain rate with threshold does not introduce any systematic bias. (2) The same results could also be derived in the application to Mt Kwanak weather radar data. In all cases with several radar bin sizes and thresholds considered, the bias was estimated to be far less than 10% of the mean of the rain gauge rain rate. (3) However, in the comparison with threshold applied to both the radar and rain gauge rain rate, the bias was estimated to be higher than 20%. That is, the systematic bias was introduced. This result indicates that the comparison with threshold applied to both the radar and rain gauge rain rate should not be used.

• 대한임베디드공학회논문지
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• 제13권4호
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• pp.169-178
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• 2018

Currently, various sensors have been used for advanced driver assistance systems. In order to overcome the limitations of individual sensors, sensor fusion has recently attracted the attention in the field of intelligence vehicles. Thus, vision and radar based sensor fusion has become a popular concept. The typical method of sensor fusion involves vision sensor that recognizes targets based on ROIs (Regions Of Interest) generated by radar sensors. Especially, because AVM (Around View Monitor) cameras due to their wide-angle lenses have limitations of detection performance over near distance and around the edges of the angle of view, for high performance of sensor fusion using AVM cameras and radar sensors the exact ROI extraction of the radar sensor is very important. In order to resolve this problem, we proposed a sensor fusion scheme based on commercial radar modules of the vendor Delphi. First, we configured multiple radar data logging systems together with AVM cameras. We also designed radar post-processing algorithms to extract the exact ROIs. Finally, using the developed hardware and software platforms, we verified the post-data processing algorithm under indoor and outdoor environments.

• 대기
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• 제33권5호
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• pp.457-475
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• 2023

Accurately predicting localized heavy rainfall is challenging without high-resolution mesoscale cloud information in the numerical model's initial field, as precipitation intensity and amount vary significantly across regions. In the Korean Peninsula, the radar observation network covers the entire country, providing high-resolution data on hydrometeors which is suitable for data assimilation (DA). During the pre-processing stage, radar reflectivity is classified into hydrometeors (e.g., rain, snow, graupel) using the background temperature field. The mixing ratio of each hydrometeor is converted and inputted into a numerical model. Moreover, assimilating saturated water vapor mixing ratio and decomposing radar radial velocity into a three-dimensional wind vector improves the atmospheric dynamic field. This study presents radar DA experiments using a numerical prediction model to enhance the wind, water vapor, and hydrometeor mixing ratio information. The impact of radar DA on precipitation prediction is analyzed separately for each radar component. Assimilating radial velocity improves the dynamic field, while assimilating hydrometeor mixing ratio reduces the spin-up period in cloud microphysical processes, simulating initial precipitation growth. Assimilating water vapor mixing ratio further captures a moist atmospheric environment, maintaining continuous growth of hydrometeors, resulting in concentrated heavy rainfall. Overall, the radar DA experiment showed a 32.78% improvement in precipitation forecast accuracy compared to experiments without DA across four cases. Further research in related fields is necessary to improve predictions of mesoscale heavy rainfall in South Korea, mitigating its impact on human life and property.

• International Journal of Contents
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• 제3권4호
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• pp.22-25
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• 2007

This paper presents a technology of information data fusion between radar and ELINT electronic intelligence system. adar get the information of the range, direction and velocity of targets, and ELINT system get the information of the direction and angular velocity of the same targets at the same place and at the same time. Since we have some common information data of targets from radar and ELINT system, we can find the target on radar is same or not on ELINT system using the information data fusions. If the target on the radar is verified with the same target on ELINT system, we get more information of the target. e can analysis and identify the target exactly and reduce an ambiguity error of unknown targets.

• Journal of Multimedia Information System
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• 제5권4호
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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.