• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.65-73
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• 2010

To observe and analyze the characteristics of cloud and precipitation properties, the Cloud physics Observation System (CPOS) has been operated from December 2003 at Daegwallyeong ($37.4^{\circ}N$, $128.4^{\circ}E$, 842 m) in the Taebaek Mountains. The major instruments of CPOS are follows: Forward Scattering Spectrometer Probe (FSSP), Optical Particle Counter (OPC), Visibility Sensor (VS), PARSIVEL disdrometer, Microwave Radiometer (MWR), and Micro Rain Radar (MRR). The former four instruments (FSSP, OPC, visibility sensor, and PARSIVEL) are for the observation and analysis of characteristics of the ground cloud (fog) and precipitation, and the others are for the vertical cloud characteristics (http://weamod.metri.re.kr) in real time. For verification of CPOS products, the comparison between the instrumental products has been conducted: the qualitative size distributions of FSSP and OPC during the hygroscopic seeding experiments, the precipitable water vapors of MWR and radiosonde, and the rainfall rates of the PARSIVEL(or MRR) and rain gauge. Most of comparisons show a good agreement with the correlation coefficient more than 0.7. These reliable CPOS products will be useful for the cloud-related studies such as the cloud-aerosol indirect effect or cloud seeding. The visibility value is derived from the droplet size distribution of FSSP. The derived FSSP visibility shows the constant overestimation by 1.7 to 1.9 times compared with the values of two visibility sensors (SVS (Sentry Visibility Sensor) and PWD22 (Present Weather Detect 22)). We believe this bias is come from the limitation of the droplet size range ($2{\sim}47\;{\mu}m$) measured by FSSP. Further studies are needed after introducing new instruments with other ranges.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1002-1004
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• 2003

A ground-based, C-band full polarimetric mobile Scatterometer system has been developed in Malaysia with collaboration between Malaysian Centre for Remote Sensing (MACRES) and Multimedia University (MMU). The main purpose of this system is to measure and monitor backscattering coefficient, ${\sigma }^0$, for earth terrain such as paddy fields, forest and soil surfaces. This paper describes the preliminary results on radar backscatter measurement from paddy field using the mobile C-band Scatterometer system. The measurement campaign was conducted at Sungai Burung area in April 2003. Real time data were collected using four polarization modes (HH, HV, VV and VH), at various incidence angles ranging from 0$^0$ to 60$^0$. The measurement data show consistent results as compared to other reports, which verify the capability of this Scatterometer system as a useful tool for remote sensing.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.12-16
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• 2018

In this work, a voltage controlled oscillator (VCO) monolithic microwave integrated circuit (MMIC) was demonstrated for 10-GHz band motion detecting sensors. The VCO MMIC was fabricated using a $2-{\mu}m$ InGap/GaAs HBT process, and the tuning of the oscillation frequency is achieved by changing the internal capacitance in the HBT, instead of using extra varactor diodes. The implemented VCO MMIC has a micro size of $500{\mu}m{\times}500{\mu}m$, and demonstrates the value of inserting the VCO into a single chip transceiver. The experimental results showed that the frequency tuning characteristic was above 30 MHz, with the excellent output flatness characteristic of ${\pm}0.2dBm$ over the tuning bandwidth. And, the VCO MMIC exhibited a phase noise characteristic of -92.64 dBc/Hz and -118.28 dBc/Hz at the 100 kHz and 1 MHz offset frequencies from the carrier, respectively. The measured values were consistent with the design values, and exhibited good performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.12
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• pp.2196-2201
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• 2007

Materials used at microwave are usually used as a dielectric with a manufacturing purpose of printed circuit boards, etc. Complex permittivity of them can be measured from attenuation constant or propagation constant of a transmission line using a microstrip line with bulk type. But as the technique recently which can manufacture to have complex permittivity and permeability demanded using nonferrous metals for powder-type grows up, we need sensors and methods which can measure characteristics of powder-type materials. So far measuring methods of permittivity and permeability with waveguide or coaxial cable are used but they have faults which have a complex measurement method and are difficult to simultaneously measure permittivity and permeability. In this paper, a simultaneous measuring method of permittivity and permeability with 2-port coaxial cable and a new proposed calculation. The proposed 2-port coaxial cable is designed to be easy to insert materials and to have a wideband. We measure permittivity and permeability of magnetic powder(Ni-Fe-Mo, Ni-Fe) which reveal its characteristic at $0.3{\sim}1.3GHz$ to identify the proposed sensor.

• Journal of Korean Vacuum Science & Technology
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• v.3 no.1
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• pp.38-42
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• 1999

Using the LOCOS process, we have fabricated the lateral type polysilicon field emission triodes with poly-Si/oxide/Si structure and investigated their current-voltage characteristics for three biasing modes of operation. The fabricated devices exhibit excellent electrical performances such as a relatively low turn-on anode voltage of 14 V at VGC = 0V, a stable and high emission current of 92${\mu}$A/triode over 90 hours, a small gate leakage current of 0.23 ${\mu}$A/triode and an outstanding transconductance of 57${\mu}$S/5triodes at VGC = 5V and VAC = 26V. these superior electrical operation is believed to be due to a large field enhancement effect, which is related to the sharp cathode tips produced by the LOCOS process as well as the high aspect ratio (height /radius ) of the cathode tip end.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.37-42
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• 1998

Latent and sensible heat fluxes over the global oceans are estimated using SSM/I (Special Sensor Microwave Imager) and AVHRR MCSST (Advanced Very High Resolution Radiometer Multi-Channel Sea Surface Temperature). The heat fluxes are computed from SSM/I wind speeds and surface humidity, the MCSST, and NCEP Reanalysis sea level pressures and 2-m temperatures from 1996 to 1997. The diabatic conditions bulk formula (Kondo, 1975) is used to compute the heat fluxes. To validate, the derived fluxes are compared to the measurements of 3 JMA buoys. The wind speeds and surface humidity derived from SSM/I have accuracies of 1.37m/s and 1.7g/kg, respectively. The heat fluxes were estimated these factors and the standard error of the latent and sensible heat fluxes are 5.53 W/m$^2$ and 3.33 W/m$^2$. The latest El-Nino phenomenon started at the beginning of 1997 and this event was larger than any others. We compare the heat fluxes in 1997 with the fluxes in 1996 and investigate the spatial movement of meteorological factors as well as the heat fluxes associated with El-Nino appearance.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.644-648
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• 2002

Though it was difficult of globally monitor latent heat flux aver the ocean for many years, the situation is rapidly changing by the use of satellite data. Since a bulk formula is used to estimate turbulent heat flux using satellite data, we need wind speed, sea surface temperature and specific humidity data. However, it is not easy to accurately estimate specific humidity using satellite data. Now several algorithms for estimating specific humidity have been proposed and applied to construct latent heat flux data sets. Latent heat flux data sets derived from satellite data such as J-OFURO, HOAPS and GSSTF are available at present. Since the algorithm and used satellite data are not the same between them. the characteristics of each data set may be different. Therefore, it is important to clarify the difference between each data set and investigate the cause of the difference in latent heat flux estimates. In this paper we summarize the present state of the art with regard to the turbulent heat flux estimation by using satellite data. Also we present the comparison results of latent heat flux fields including not only satellite-derived flux fields but also analysis fields.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.171-182
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• 2001

Travel Time is an important characteristic of traffic conditions in a road network. Currently, there are so many road users to get a unsatisfactory traffic information that is provided by existing collection systems such as, Detector, Probe car, CCTV and Anecdotal Report. This paper presents the results achieved with Data Fusion Model, Hybrid Neuro Fuzzy System for on - line estimation of travel times using RTMS(Remote Traffic Microwave Sensor) and Probe Data in the signalized arterial road. Data Fusion is the most important process to compose the various of data which can present real value for traffic situation and is also the one of the major process part in the TIC(Traffic Information Center) for analyzing and processing data. On-line travel time estimation methods(FALEM) on the basis of detector data has been evaluated by real value under KangNam Test Area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.472-477
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• 2017

Oil spills cause a lot of damage to the environment. Oil destroys the water environment and ecosystem in a very short period of time once they are contaminated by it, it takes a lot of time to recover from the contamination and the cleaning process is very difficult. Therefore, oil detectors are greatly needed as they can monitor any oil spills over the sea, rivers, and lakes. There are two kinds of technology available for detecting oil, viz. the contact and non-contact types. The former is based on the use of the conductivity, capacitance and microwaves, while the latter employs infrared, UV, laser, optic and radar technologies. As there are also various hurdles in the measuring of oil on water, such as the presence of waves, refraction of light, temperature and saltiness, it is imperative to select the right oil detector which is appropriate for the specific environment. In this study, a contact type oil detector is developed, which can be used in oil related industries, such as refineries, petrochemical companies, and power generation stations. The detector is made up of the sensor module, which floats on the water, and the controller which processes the signal coming from the sensor module and displays it. It is designed in such a way that the existence of oil is detected through the sensor and the change in the permittivity is observed to determine the volume and type of spilled oil.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.65-65
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• 2002

In remote sensing, images are acquired over the same area by sensors of different spectral ranges (from the visible to the microwave) and/or with different number, position, and width of spectral bands. These images are generally partially redundant, as they represent the same scene, and partially complementary. For many applications of image classification, the information provided by a single sensor is often incomplete or imprecise resulting in misclassification. Fusion with redundant data can draw more consistent inferences for the interpretation of the scene, and can then improve classification accuracy. The common approach to the classification of multisensor data as a data fusion scheme at pixel level is to concatenate the data into one vector as if they were measurements from a single sensor. The multiband data acquired by a single multispectral sensor or by two or more different sensors are not completely independent, and a certain degree of informative overlap may exist between the observation spaces of the different bands. This dependence may make the data less informative and should be properly modeled in the analysis so that its effect can be eliminated. For modeling and eliminating the effect of such dependence, this study employs a strategy using self and conditional information variation measures. The self information variation reflects the self certainty of the individual bands, while the conditional information variation reflects the degree of dependence of the different bands. One data set might be very less reliable than others in the analysis and even exacerbate the classification results. The unreliable data set should be excluded in the analysis. To account for this, the self information variation is utilized to measure the degrees of reliability. The team of positively dependent bands can gather more information jointly than the team of independent ones. But, when bands are negatively dependent, the combined analysis of these bands may give worse information. Using the conditional information variation measure, the multiband data are split into two or more subsets according the dependence between the bands. Each subsets are classified separately, and a data fusion scheme at decision level is applied to integrate the individual classification results. In this study. a two-level algorithm using hierarchical clustering procedure is used for unsupervised image classification. Hierarchical clustering algorithm is based on similarity measures between all pairs of candidates being considered for merging. In the first level, the image is partitioned as any number of regions which are sets of spatially contiguous pixels so that no union of adjacent regions is statistically uniform. The regions resulted from the low level are clustered into a parsimonious number of groups according to their statistical characteristics. The algorithm has been applied to satellite multispectral data and airbone SAR data.