• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.473-480
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• 2005

A three axes marine satellite antenna has been developed. As a design step, a CAD model for the antenna has been created according to the design requirements. Kinematic analyses are carried out to insure design specification and to check collision detection of the CAD model. Marine satellite antennas experience base motions, and a relevant control system should control the three antenna axis to point to the satellites accurately. A sensor fusion algorithm and a PIDA (Proportional, Integral, Derivative, Acceleration) control algorithm are designed and implemented to control the yaw, level, and cross-level angle of a small size satellite marine antenna. Antenna stabilization control experiments are performed using a test simulator which gives the antenna base motions. Experimental results show small pointing errors, which is less than 0.2 degree for the level, cross-level, and yaw axis.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.780-785
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• 2002

As the KOMPSAT-1 satellite can roll tilt up to $\pm$45$^{\circ}$, we have analyzed some EOC images taken at different tilt angles fur this study. The required ground coordinates for bundle adjustment and geometric accuracy, are read from the digital map produced by the National Geography Institution, at a scale of 1:5, 000. These are the steps taken for the tilting angle of KOMPSAT-1 satellite to be present in the evaluation of the accuracy of the geometric of each different stereo image data: Firstly, as the tilting angle is different in each image, the satellite dynamic characteristic must be determined by the sensor modeling. Then the best sensor modeling equation is determined. The result of this research, the difference between the RMSE values of individual stereo images is due more the quality of image and ground coordinates than to the tilt angle. The bundle adjustment using three KOMPSAT-1 stereo pairs, first degree of polynomials for modeling the satellite position were sufficient.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.217-219
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• 2010

Sensor modeling is the basic step to extract and to use the information from satellite images. Sensor modeling requires ground control points. If we use a single image, we have limitations on modeling about images captured from regions that we can not approach or take GCPs. In this research, we use strip images to do sensor modeling by two methods. At first, we apply sensor modeiling to single image and apply the results by extrapolation. Next, we consider strip images to single image. As a result, we find the second method is more accurate about whole image.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.81-88
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• 2007

The geometry of satellite image captured by linear CCD sensor is different from that of frame camera image. The fact that the exterior orientation parameters for satellite image with linear CCD sensor varies from scan line by scan line, causes the difference of image geometry between frame and linear CCD sensor. Therefore, we need the epipolar geometry for linear CCD image which differs from that of frame camera image. In this paper, we proposed a method of resampling linear CCD satellite image in epipolar geometry under the assumption that image is not formed in perspective projection but in parallel projection, and the sensor model is a 2D affine sensor model based on parallel projection. For the experiment, IKONOS stereo images, which are high resolution linear CCD images, were used and tested. As results, the spatial accuracy of 2D affine sensor model is investigated and the accuracy of epipolar resampled image with RFM was presented.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1541-1551
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• 2023

Radiometric calibration is a fundamental step in ocean color remote sensing since the step to derive solar radiance spectrum in visible to near-infrared wavelengths from the sensor-observed electromagnetic signals. Generally, satellite sensor suffers from degradation over the mission period, which results in biases/uncertainties in radiometric calibration and the final ocean products such as water-leaving radiance, chlorophyll-a concentration, and colored dissolved organic matter. Therefore, the importance of radiometric calibration for the continuity of ocean color satellites has been emphasized internationally. This study introduces an approach to improve the radiometric calibration algorithm for the visible bands of the Geostationary Ocean Color Imager-II (GOCI-II) satellite with a focus on stability. Solar Diffuser (SD) measurements were employed as an on-orbit radiometric calibration reference, to obtain the continuous monitoring of absolute gain values. Time series analysis of GOCI-II absolute gains revealed seasonal variations depending on the azimuth angle, as well as long-term trends by possible sensor degradation effects. To resolve the complexities in gain variability, an azimuth angle correction model was developed to eliminate seasonal periodicity, and a sensor degradation correction model was applied to estimate nonlinear trends in the absolute gain parameters. The results demonstrate the effects of the azimuth angle correction and sensor degradation correction model on the spectrum of Top of Atmosphere (TOA) radiance, confirming the capability for improving the long-term stability of GOCI-II data.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.518-523
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• 2002

Nowadays the Rational Function Model (RFM), an abstract sensor model, is substituting physical sensor models for highly complicated imaging geometry. But RFM is algorithm to be required many Ground Control Points (GCP). In case of RFM of the third order, At least forty GCP are required far RFM generation. The purpose of this study is to research more efficient algorithm on GCP and accurate algorithm similar to RFM. The Polynomial Camera Model is relatively accurate and requires a little GCP in comparisons of RFM. This paper introduces how to generate Polynomial Camera Model and fundamental algorithms for construction of 3-D topographic data using the Polynomial Camera Model information in the Kompsat stereo pair and describes how to generate the 3-D ground coordinates by manual matching. Finally we tried to extract height information for the whole image area with the stereo matching technique based on the correlation.

• Journal of Astronomy and Space Sciences
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• v.17 no.2
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• pp.267-276
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• 2000

PSS(Pyramidal type 2-axes Analog Sun Sensor) which will be used for KAISTSAT-4 is designed to be small, light, low in power consumptions, and adequate for small satellite attitude sensor. The PSS for the KAISTSAT-4 consists of the pyramidal structure, solar cells and amplifier. The pyramidal structure is suitable for the 2-axes sensing, Solar cells are made up of a rectangular shape of crystal silicon. The PSS measures the angle of incident light and initial satellite attitude measurement, and provides an alarm for the sunlight-sensitive payloads. This paper explains the PSS structure and the characteristic test result about the PSS with $\pm$$50^{\circ}$in FOV, less than $\pm$$3^{\circ}$in accuracy.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.33-44
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• 2001

The paper presents several satellite models and satellite image decomposition methods for inaccessible area where ground control points can hardly acquired in conventional ways. First, 10 different satellite sensor models, which were extended from collinearity condition equations, were developed and then behavior of each sensor model was investigated. Secondly, satellite images were decomposed and also pseudo images were generated. The satellite sensor model extended from collinearity equations was represented by the six exterior orientation parameters in $1^{st}$, $2^{nd}$ and $3^{rd}$ order function of satellite image row. Among them, the rotational angle parameters such as $\omega$(omega) and $\Phi$(phi) correlated highly with positional parameters could be assigned to constant values. For inaccessible area, satellite images were decomposed, which means that two consecutive images were combined as one image, The combined image consists of one satellite image with ground control points and the other without ground control points. In addition, a pseudo image which is an imaginary image, was prepared from one satellite image with ground control points and the other without ground control points. In other words, the pseudo image is an arbitrary image bridging two consecutive images. For the experiments, SPOT satellite images exposed to the similar area in different pass were used. Conclusively, it was found that 10 different satellite sensor models and 5 different decomposed methods delivered different levels of accuracy. Among them, the satellite camera model with 1st order function of image row for positional orientation parameters and rotational angle parameter of kappa, and constant rotational angle parameter omega and phi provided the best 60m maximum error at check point with pseudo images arrangement.

• Journal of Space Technology and Applications
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• v.1 no.3
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• pp.356-363
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• 2021

It was common knowledge in textbooks that images acquired using mid-infrared ray were not suitable for measuring temperature near room temperature. But a recent satellite image using a mid-infrared sensor show the possibility that the result measured using the mid-infrared sensor can also measure the temperature near room temperature. In this paper, the possibility and accuracy of extraction room temperature information from satellite images with mid-infrared sensors are reviewed. The mid-infrared satellite image reviewed in this paper showed the temperature of room temperature well, and regarding the reliability as an absolute value of the measured temperature, the effect of the heat transfer amount due to the direct reflection of sunlight on the surface and the effect of the infrared absorption amount absorbed in the atmosphere can be seen as a relatively small or constant value. However, the problem of uncertainty in the radiation coefficient due to physical properties, which is the limit of the non-contact thermometer, remained a problem to be solved.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.1025-1032
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• 2006

Sensor modeling of high-resolution satellites is a prerequisite procedure for mapping and GIS applications. Sensor models, describing the geometric relationship between scene and object, are divided into two main categories, which are rigorous and approximate sensor models. A rigorous model is based on the actual geometry of the image formation process, involving internal and external characteristics of the implemented sensor. However, approximate models require neither a comprehensive understanding of imaging geometry nor the internal and external characteristics of the imaging sensor, which has gathered a great interest within photogrammetric communities. This paper described a comparison between rigorous and various approximate sensor models that have been used to determine three-dimensional positions, and proposed the appropriate sensor model in terms of the satellite imagery usage. Through the case study of using IKONOS satellite scenes, rigorous and approximate sensor models have been compared and evaluated for the positional accuracy in terms of acquirable number of ground controls. Bias compensated RFM(Rational Function Model) turned out to be the best among compared approximate sensor models, both modified parallel projection and parallel-perspective model were able to be modelled with a small number of controls. Also affine transformation, one of the approximate sensor models, can be used to determine the planimetric position of high-resolution satellites and perform image registration between scenes.