• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.4
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• pp.331-339
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• 2010

To analyze and verify the performance of a MWR(Missile Warning Radar) of a GVWS(Ground Vehicle Weapon System), there is a need to make a simulator which can conduct the linked and engaged test virtually using the simulated signals. In this paper, a method of the simulator design for MWR is proposed to solve the above need. The SP(Signal Processor) part which generates the simulated signals and analyzes the algorithms is explained. The RF(Radio Frequency) part which transforms IF(Intermediate Frequency) signals into RF signals, radiates RF signals, and controls the linked equipments is also explained. The utility of the proposed design is proved by presenting the results of the contributions to the development of MWR.

• Atmosphere
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• v.17 no.3
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• pp.291-298
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• 2007

The precipitable water vapors (PWVs) obtained from Global Positioning System (GPS) and Microwave Radiometer (MWR) measurements have been compared for validation of precision of the GPS PWV at Daegwallyoung station for 21 days from Sep. 30 to Oct. 20, 2006. The GPS PWV is estimated using the delay of GPS signals due to the water vapor in the atmosphere with a local mean temperature equation, called HP model, and the MWR PWV by the combinational radiance observation of two channels (23.8 and 31.4 GHz). During the co-observation period, the MWR and GPS PWV show a similar trend, and the bias between the PWVs is 1.7 mm on average. When the bias is removed, the PWV of GPS gives good agreement with that of MWR, having about 1 mm for both the standard deviation and RMS error between the GPS and MWR PWV.

• Korean Journal of Optics and Photonics
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• v.22 no.6
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• pp.283-290
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• 2011

A Raman LIDAR system has been designed and constructed for quantitative measurement of water vapor mixing ratio. The comparison with commercial microwave radiometer and global navigation satellite system(GNSS) was performed for the precipitable water vapor(PWV) profile and total PWV. The result shows that the total GNSS-PWV and LIDAR-PWV have good correlation with each other. But, there is small difference between the two methods because of maximum measurement height in LIDAR and the GNSS method. There are some significant differences between Raman and MWR when the water vapor concentration changes quickly near the boundary layer or at the edge of a cloud. Finally we have decided that MWR cannot detect spatial changes but LIDAR can measure spatial changes.

• Journal of Astronomy and Space Sciences
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• v.29 no.1
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• pp.1-10
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• 2012

In this study, global positioning system (GPS)-derived precipitable water vapor (PWV) and microwave radiometer (MWR)-measured integrated water vapor (IWV) were compared and their characteristics were analyzed. Comparing those two quantities for two years from August 2009, we found that GPS PWV estimates were larger than MWR IWV. The average difference over the entire test period was 1.1 mm and the standard deviation was 1.2 mm. When the discrepancies between GPS PWV and MWR IWV were analyzed depending on season, the average difference was 0.7 mm and 1.9 mm in the winter and summer months, respectively. Thus, the average difference was about 2.5 times larger in summer than that in winter. However, MWR IWV measurements in the winter months were over-estimated than those in the summer months as the water vapor content got larger. The results of the diurnal analysis showed that MWR IWV was underestimated in the daytime, showing a difference of 0.8 mm. In the early morning hours, MWR IWV has a tendency to be over-estimated, with a difference of 1.3 mm with respect to GPS PWV.

• Journal of Coastal Disaster Prevention
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• v.4 no.4
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• pp.189-196
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• 2017

Ocean Research Stations (ORSs) is the ocean platform type observation towers and measured oceanic, atmospheric and environmental data. These station located on the offshore area far from the coast, so they can produce the data without land effect. This study focused to improve the wave data quality of ORS station. The wave observations at ORSs are used by the C-band (5.8 GHz, 5.17 cm) MIROS Wave and Current Radar (MWR). MWR is convenient to maintenance and produce reliability wave data under bad weather conditions. MWR measured significant wave height, peak wave period, peak wave direction and 2D wave spectrum, so it's can provide wave information for researchers and engineers. In order to improve the reliability of MWR wave data, Datawell Waverider Buoy was installed near the one ORS (Socheoncho station) during 7 months and validate the wave data of MWR. This study found that the wave radar tend to be overestimate the low wave height under wind condition. Firstly, this study carried out the wave Quality Control (QC) using wind data, however the quality of wave data was limited. So, this study applied the four filters (Correlation Check, Direction Filter, Reduce White Noise and Phillips Check) of MWR operating software and find that the filters effectively improve the wave data quality. After applying 3 effective filters in combination, the RMSE of significant wave height decreased from 0.81m to 0.23m, by 0.58m and Correlation increased from 0.66 to 0.96, by 0.32, so the reliability of MWR significant wave height was significantly improved.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.8
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• pp.1159-1164
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• 2010

The current maritime data communications mainly depend on radio and satellite which have restrictions on data rate and cost. That leads to needs of novel relatively-high-speed data communication systems at sea just like on land. This paper proposes a routing protocol (MWR) for newly designed model of ship-to-ship communication networks at sea. The MWR protocol finds out an optimal route by selecting an optimal network for each specific application from overlapped networks of available wireless media at sea.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.1
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• pp.93-101
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• 2008

It is difficult for a MWR(Missile Warning Radar) to perform a threat decision accurately since there is no tracking part which gives more accurate threat information to the MWR. In this paper, the threat decision algorithm is proposed using an azimuth angular rate to improve the accuracy. The azimuth angular rate is dependent upon the direction of an approaching target. The target is classified into a threat or non-threat using a boundary condition of the azimuth angular rate. The boundary condition is determined using the Monte-Carlo simulation. The performance of the proposed algorithm is evaluated using this condition at field tests of MWR. The efficiency of the proposed method for the threat decision is proved by comparing the results of field tests with the simulation results.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.228-240
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• 2018

Solar energy is calculated using meteorological (14 station), ceilometer (2 station) and microwave radiometer (MWR, 7 station)) data observed from the Weather Information Service Engine (WISE) on the Seoul metropolitan area. The cloud optical thickness and the cloud fraction are calculated using the back-scattering coefficient (BSC) of the ceilometer and liquid water path of the MWR. The solar energy on the surface is calculated using solar radiation model with cloud fraction from the ceilometer and the MWR. The estimated solar energy is underestimated compared to observations both at Jungnang and Gwanghwamun stations. In linear regression analysis, the slope is less than 0.8 and the bias is negative which is less than $-20W/m^2$. The estimated solar energy using MWR is more improved (i.e., deterministic coefficient (average $R^2=0.8$) and Root Mean Square Error (average $RMSE=110W/m^2$)) than when using ceilometer. The monthly cloud fraction and solar energy calculated by ceilometer is greater than 0.09 and lower than $50W/m^2$ compared to MWR. While there is a difference depending on the locations, RMSE of estimated solar radiation is large over $50W/m^2$ in July and September compared to other months. As a result, the estimation of a daily accumulated solar radiation shows the highest correlation at Gwanghwamun ($R^2=0.80$, RMSE=2.87 MJ/day) station and the lowest correlation at Gooro ($R^2=0.63$, RMSE=4.77 MJ/day) station.

• Atmosphere
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• v.17 no.1
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• pp.101-108
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• 2007

To observe and analyze the cloud and fog characteristics, the METeorological Research Institute (METRI) has established the Cloud Physics Observation System (CPOS) by implementing the cloud observation instruments: Forward Scattering Spectrometer Probe (FSSP), PARticle SIze and VELocity (PARSIVEL), Microwave Radiometer (MWR), Micro Rain Radar (MRR), and 3D-AWS at the Daegwallyeong Enhanced Mountain Weather Observation Center. The cloud-related products of CPOS and the validation status for the size distribution of FSSP, the precipitable water of MWR, and the rainfall rate of MRR and PARSIVEL are described.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.2
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• pp.135-145
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• 2020

Wave observation is widely used to direct observation method for observing the water surface elevation using wave buoy or pressure gauge and remote-sensing wave observation method. The wave buoy and pressure gauge can produce high-quality wave data but have disadvantages of the high risk of damage and loss of the instrument, and high maintenance cost in the offshore area. On the other hand, remote observation method such as radar is easy to maintain by installing the equipment on the land, but the accuracy is somewhat lower than the direct observation method. This study investigates the data quality of MIROS Wave and Current Radar (MWR) installed at Dokdo and improve the data quality of remote wave observation data using the wave buoy (CWB) observation data operated by the Korea Meteorological Administration. We applied and developed the three types of wave data quality control; 1) the combined use (Optimal Filter) of the filter designed by MIROS (Reduce Noise Frequency, Phillips Check, Energy Level Check), 2) Spike Test Algorithm (Spike Test) developed by OOI (Ocean Observatories Initiative) and 3) a new filter (H-Ts QC) using the significant wave height-period relationship. As a result, the wave observation data of MWR using three quality control have some reliability about the significant wave height. On the other hand, there are still some errors in the significant wave period, so improvements are required. Also, since the wave observation data of MWR is different somewhat from the CWB data in high waves of over 3 m, further research such as collection and analysis of long-term remote wave observation data and filter development is necessary.