• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.441-444
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• 2008

This paper describes the development of a circularly polarized microstrip antenna, as a part of the Circularly Polarized Synthetic Aperture Radar (CP-SAR) sensor which is currently under developed at the Microwave Remote Sensing Laboratory (MRSL) in Chiba University. CP-SAR is a new type of sensor developed for the purpose of remote sensing. With this sensor, lower-noise data/image will be obtained due to the absence of depolarization problems from propagation encounter in linearly polarized synthetic aperture radar. As well the data/images obtained will be investigated as the Axial Ratio Image (ARI), which is a new data that hopefully will reveal unique various backscattering characteristics. The sensor will be mounted on an Unmanned Aerial Vehicle (UAV) which will be aimed for fundamental research and applications. The microstrip antenna works in the frequency of 1.27 GHz (L-Band). The microstrip antenna utilized the proximity-coupled method of feeding. Initially, the optimization process of the single patch antenna design involving modifying the microstrip line feed to yield a high gain (above 5 dBi) and low return loss (below -10 dB). A minimum of 10 MHz bandwidth is targeted at below 3 dB of Axial Ratio for the circularly polarized antenna. A planar array from the single patch is formed next. Consideration for the array design is the beam radiation pattern in the azimuth and elevation plane which is specified based on the electrical and mechanical constraints of the UAV CP-SAR system. This research will contribute in the field of radar for remote sensing technology. The potential application is for landcover, disaster monitoring, snow cover, and oceanography mapping.

• Proceedings of the KSRS Conference
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• v.1
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• pp.38-38
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• 2006

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.367-372
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• 2006

Cloud detection algorithm is being developed as primary one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-IR and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithms and preliminary test results of both algorithms.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.587-592
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• 2002

A new digital correlator fur an airborne synthetic aperture radiometer was designed in order to replace the conventional analog correlator unit which will become very complicated while the number of channels is increasing. The digital correlator uses digital IQ demodulator instead of the intermediate frequency (IF) phase shifter to make the correlation processing performed digitally at base band instead of analogly at IF. This technique has been applied to the digital receiver in softradio. The down-converted IF signals from each pair of receiver channels become low rate base-band digital signals after under-sampled, Digitally Down-Converted (DDC), decimated and filtered by FIR filters. The digital signals are further processed by two digital multipliers (complex correlation), the products are integrated by the integrators and finally the outputs from the integrators compose of the real part and the imaginary part of a sample of the visibility function. This design is tested by comparing the results from digital correlators and that from analog correlators. They are agreed with each other very well. Due to the fact that the digital correlators are realized with the help of Analog-Digital Converter (ADC) chips and the FPGA technology, the realized volume, mass, power consumption and complexity turned out to be greatly reduced compared with that of the analog correlators. Simulations show that the resolution of ADC has an influence on the synthesized antenna patterns, but this can be neglected if more than 2bit is used.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1069-1078
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• 2014

This study presents the design and implementation of a web-based remote laboratory for a multi-mode single-leg power converter, which is a topic in advanced power electronics course. The proposed laboratory includes an experimental test rig with a multi-mode single-leg power converter and its driver circuits, a measurement board, a control platform, and a LabVIEW-based user interface program that is operated in the server computer. Given that the proposed web-based remote laboratory is based on client/server architecture, the experimental test rig can be controlled by a client computer with Internet connection and a standard web browser. Although the multi-mode single-leg power converter can work at four different modes (main boost, buck-boost, boost-boost, and battery boost modes), only the buck-boost mode is used in the experiment because of page limit. Users can choose the control structure, control parameters, and reference values, as well as obtain graphical results from the user interface software. Consequently, the feedbacks received from students who conducted remote laboratory studies indicate that the proposed laboratory is a useful tool for both remote and traditional education.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.638-643
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• 2002

MODIS (MODerate-resolution Imaging Spectroradiometer) onboard the first Earth Observing System (EOS) satellite, Terra, was launched successfully at the end of 1999. The direct broadcast MODIS data has been received and utilized in Korea Meteorological Administration (KMA) since february 2001. This study introduces utilizations of this data, especially for the derivation of sea surface temperature (SST). To produce the MODIS SST operationally, we used a simple cloud mask algorithm and MCSST algorithm. By using a simple cloud mask algorithm and by assumption of NOAA daily SST as a true SST, a new set of MCSST coefficients was derived. And we tried to analyze the current NASA's PFSST and new MCSST algorithms by using the collocated buoy observation data. Although the number of collocated data was limited, both algorithms are highly correlated with the buoy SST, but somewhat bigger bias and RMS difference than we expected. And PFSST uniformly underestimated the SST. Through more analyzing the archived and future-received data, we plan to derive better MCSST coefficients and apply to MODIS data of Aqua that is the second EOS satellite. To use the MODIS standard cloud mask algorithm to get better SST coefficients is going to be prepared.

• Proceedings of the KSRS Conference
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• v.1
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• pp.200-203
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• 2006

Cloud detection algorithm is being developed as major one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-1R and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithm and preliminary test result of both algorithms.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.135-139
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• 1999

Wind velocity is one of the primary variables for describing atmospheric state from GMS-5. And its accurate depiction is essential for operational weather forecasting and for initialization of NWP(Numerical Weather Prediction) models. The aim of this research is to incorporate imagery from other available spectral channels and examine the error characteristics of winds derived from these images. Multi spectral imagery from GMS-5 was used for this purpose and applied to Korean region with together BoM(Bureau of Meteorology). The derivation of wind velocity estimates from low and high resolution visible, split window infrared, and water vapor images, resulted in improvements in the amount and quality of wind data available for forecasting.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.461-463
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• 2003

The information on the cloud presence within a instantaneous field of view is the first step toward the derivation of many other geophysical parameters. Here, we first applied the current MODIS cloud detection algorithm developed by University of Wisconsin and compared the results to a visual interpretation of composite data, especially during the daytime. Most of cases, the detection algorithm performs very well, except a few cases with over-detection. One of the reasons for the false detection is due to the time independent use of land information which affects the threshold values of visible channel test. In the presentation, we show detailed analysis of the current cloud detection algorithm and suggest possible way to overcome the current shortfall.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.307-314
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• 1998

To examine the detectability of the yellow sand and/or aerosol from China crossing over the Yellow Sea within the range of OSMI wavelengths(400-900 nm), we have investigated the optical characteristics of aerosols in yellow sand events observed on April, 1998 in Seoul. The spectral reflectance(%) and aerosol optical thickness in the range of Visible(VIS) and near Infrared (NIR) wavelengths were derived from the measurements of solar radiation using the GER-2600 spectroradiometer and sunphotometer during the April, 1798. The average spectral reflectance for the yellow sand events is over 40% and higher around 14:30 than 12:00 LST, but that for clear days is about 20% both at 12:00 and 14:30 LST in the range of 500-900 nm. The aerosol optical thickness at 501 nm varied from 0.25 on very clear day to 1.01 during a so-called "yellow-sand" episode and that for 673 nm varied from 0.14 to 0.92, respectively.