• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.150-156
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• 2011

Smart Highway is a next generation highway that significantly improves a traffic safety, reduces incidence of traffic accidents, and supports intelligent and convenient driving environments so that drivers can drive at high speeds in safety. In order to implement smart highway, it is required to gather a large amount of data including conditions of a road and the status of vehicles, and other useful data. To provide situation information of highway, it has been gathered traffic information using optical sensors(CCTV, etc.). However, this technique has problems such as the problem of information gathering, lack of accuracy depending on weather conditions and limitation of maintenance. It needs radar system which has not effect on environmental change and algorithm processing technique in order to provide information for a safety driving to driver and car. In this paper, it is used radar with 9.4GHz to test performance of a road surface and developed radar system for detecting test. And we compared and analyzed a performance of data acquired from each radar through computer simulation.

• Journal of Korea Water Resources Association
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• v.39 no.4 s.165
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• pp.321-334
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• 2006

The need for economical and accurate presentations of equivalent radar reflectivity( $Z_e$) data in an orthogonal coordinate system has existed for some time. So, in this study, a fast and efficient procedure has been developed which allows the systematic interpolation of digital reflectivity data from radar space into Cartesian space. At first, QC(Quality Control) of radar data has been executed for extracting uncontaminated Constant Altitude Plan Position Indicator(CAPPI) data. The algorithm is designed so that only one ordered pass through the original Plan Position Indicator(PPI) scan data is necessary to complete the interpolation process. The model can calculate various resolution and altitude reflectivity data for many kinds of hydrological usage.

• Journal of Advanced Navigation Technology
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• v.10 no.2
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• pp.173-180
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• 2006

An airborne radar is an essential aviation electronic system of the aircraft to perform various missions in all weather environments. This paper presents the design, development, and test results of the multi-mode pulsed Doppler radar system test model for helicopter-borne flight test. This radar system consists of 4 LRU units, which include ANTU(Antenna Unit), TRU(Tx Rx Unit), RSDU(Radar Signal & Data Processing Unit) and DISU(Display Unit). The developed technologies include the TACCAR processor, planar array antenna, TWTA transmitter, coherent I/Q detector, digital pulse compression, DSP based Doppler FFT filtering, adaptive CFAR, IMU, and tracking capability. The design performance of the developed radar system is verified through various helicopter-borne field tests including MTD (Moving Target Detector) capability for the Doppler compensation due to the moving platform motion.

• Journal of the Korean earth science society
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• v.33 no.5
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• pp.377-394
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• 2012

To elucidate the mechanism associated with the development of heavy precipitation system, a field experiment was carried out in Jejudo (or Jeju Island) and Marado, Korea from 22 June to 12 July 2006. The synoptic atmospheric conditions were analyzed using the National Centers for Environmental Prediction-National Center for Atmospheric Research's (NCEP/NCAR) reanalyzed data, weather maps, and sounding data. The kinematic characteristics of each precipitation system were investigated by dual Doppler radar analysis. During the field experiment, data of four precipitation events with more than 20 mm rainfall were collected. In F case (frontal precipitation), a typical Changma front was dominant and the observation field was fully saturated. However there was no convective instability near the surface. LF case (low pressure accompanied with Changma front) showed strong convective instability near the surface, while a strong convergence corresponded to the low pressure from China accompanied with Changma front. In FT case (Changma front indirectly influenced by typhoon), the presence of a convective instability indicated the transport of near surface, strong additional moisture from the typhoon 'EWINIAR'. The convergence wind field was ground to be located at a low level. The convective instability was not significant in T case (precipitation of the typhoon 'EWINIAR'), since the typhoon passed through Jejudo and the Changma front was disappeared toward the northeastern region of the Korean peninsula. The kinematic (convergence and divergence) characteristics of wind fields, convective instability, and additional moisture inflow played important roles in the formation and development of heavy precipitation.

• 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).

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1405-1423
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• 2021

Precipitation is one of the main factors that affect water and energy cycles, and its estimation plays a very important role in securing water resources and timely responding to water disasters. Satellite-based quantitative precipitation estimation (QPE) has the advantage of covering large areas at high spatiotemporal resolution. In this study, machine learning-based rainfall intensity models were developed using Himawari-8 Advanced Himawari Imager (AHI) water vapor channel (6.7 ㎛), infrared channel (10.8 ㎛), and weather radar Column Max (CMAX) composite data based on random forest (RF). The target variables were weather radar reflectivity (dBZ) and rainfall intensity (mm/hr) converted by the Z-R relationship. The results showed that the model which learned CMAX reflectivity produced the Critical Success Index (CSI) of 0.34 and the Mean-Absolute-Error (MAE) of 4.82 mm/hr. When compared to the GeoKompsat-2 and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) rainfall intensity products, the accuracies improved by 21.73% and 10.81% for CSI, and 31.33% and 23.49% for MAE, respectively. The spatial distribution of the estimated rainfall intensity was much more similar to the radar data than the existing products.

• Journal of Korea Water Resources Association
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• v.42 no.12
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• pp.1039-1052
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• 2009

Radar measurement with high temporal and spatial resolutions can be a valuable source of data, especially in the areas where rain gauge installment is not practical. However, this kind of data brings with it many errors. The objective of this paper is to propose a method to evaluate statistically the quantitative and qualitative accuracy at different radar ranges, temporal intervals and raingage densities and use a bias adjustment technique to improve the quality of radar rainfall for the purpose of hydrological application. The method is tested with the data of 2 storm events collected at Jindo (S band) and Kwanak (C band) radar stations. The obtained results show that the accuracy of radar rainfall estimation increases when time interval rises. Radar data at the shorter range seems to be more accurate than the further one, especially for C-band radar. Using the Monte Carlo simulation experiment, we find out that the sampling error of the bias between radar and gauge rainfall reduces nonlinearly with increasing raingage density. The accuracy can be improved considerably if the real-time bias adjustment is applied, making adjusted radar rainfall to be adequately good to apply for hydrological application.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.324-327
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• 2008

Microwave remote sensing has great potential, especially in monsoon Asia, since optical observations are often hampered by cloudy conditions. The radar backscattering characteristics of rice crop were investigated with a ground-based automatic scatterometer system. The system was installed inside a shelter in an experimental paddy field at the National Institute of Agricultural Science and Technology (NIAST) before transplanting. The rice cultivar was a kind of Japonica type, called Chuchung. The scatterometer system consists of X-band antennas, HP8720D vector network analyzer, RF cables, and a personal computer that controls frequency, polarization and data storage. This system automatically measures fully-polarimatric backscattering coefficients of rice crop every 10 minutes, accompanied by a digital camera that takes pictures in a fixed position with the same interval. The backscattering coefficients were calculated by applying a radar equation. Plant variables, such as leaf area index (LAI), biomass, plant height and weather conditions were measured periodically throughout the rice growth season. We have performed polarimetric decomposition of paddy data such as single, double and volume scattering to extract the scattering information effectively. We investigated the relationships between backscattering coefficients and the plant variables.

• Journal of Wetlands Research
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• v.14 no.3
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• pp.385-397
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• 2012

A grid based physically distributed model analyzes rainfall-runoff using physical parameters and grid-typed spatial and hydrological data. This study have developed a real time runoff modelling system using GRM RT(Grid based Rainfall-runoff Model Real Time) which is a real time flow analysis module in GRM, a grid based physically distributed rainfall-runoff model. Weather radar data received in real time are calibrated by using real time AWS from Korea Meteorological Administration(KMA), and they are applied to real time runoff modeling. And the runoff model is calibrated by using observed discharges from a water level gauge in real time. This study have designed and implemented the databases necessary to construct the real time runoff modelling system, and established the process of a real time runoff modelling. And the performances of the developed system have been evaluated. The system have been applied to Nerinheon watershed located in the upstream of Soyanggang Dam and the application results are evaluated.

• Journal of Korea Water Resources Association
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• v.48 no.12
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• pp.995-1009
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• 2015

Weather radar rainfall data has been recognized for making valuable contributions to short-term flood forecasting and management over the past decades. There are several advantages to better monitoring rainfall in ungauged area compared to ground-based rain gauges with which spatial patterns of the rainfall are not effectively identified. Hence, this study aims to develop a new scheme to forecast spatio-temporal rainfall field. The proposed model was based on an advection scheme to track wind patterns and velocity. The results showd a promising forecasting skill with quantitative and qualitative measures. It was confirmed that the forecasted rainfall may be effectively used an input data for a distributed hydrological model.