• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.8
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• pp.624-631
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• 2018

To meet the requirements of various satellite synthetic aperture radar(SAR) system performance parameters, the characteristics of the antenna pattern should be analyzed. In this paper, we propose a method to improve the SAR system performance using an effective technique for optimizing antenna pattern synthesis in the presence of element failure. The desired antenna pattern can be synthesized by referring to the optimized antenna mask templates using the particle swarm optimization algorithm. In the simulation, the performance of the proposed method is verified by analyzing characteristics related to the SAR system performance parameters using antenna pattern regeneration.

• Aerospace Engineering and Technology
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• v.10 no.2
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• pp.37-48
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• 2011

Synthetic Aperture Radar(SAR) is a powerful and well established microwave remote sensing technique which enables high resolution measurement of Earth surface independent of weather conditions and sunlight illumination. KARI has been developing the first Korea SAR satellite which is scheduled to be launched in this year. The SAR satellite mainly consists of the bus platform and SAR payload. Most of all, the RF compatible design during the design phase and the verification of the RF compatibility during the testing phase is very important procedure for the in-orbit performance guarantee because the SAR payload radiates high power through the SAR antenna. In this study, the SAR satellite design criteria and verification procedure for the RF compatibility are described. In addition, this paper describes the RF full radiation testing (RF auto-compatibility testing) for the verification of the RF performance robustness, the testing configuration, and the test results.

• Korean Journal of Remote Sensing
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• v.16 no.1
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• pp.13-24
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• 2000

SAR imagery usually reveals the influence of antenna look-direction on the delineation of geological structures. In this study, the look-direction bias in SAR image is quantitatively analyzed specifically for geological lineament study. Geologic lineaments are estimated using both Landsat TM and JERS-1 SAR images over the study area to quantitatively compare and analyze the look-direction bias in the SAR image. The standard geologic lineaments in the study area are established from lineaments estimated from TM images, field mapping, and fault lines in a published geologic map. The results show that lineaments normal to radar look-direction are extremely well enhanced while those parallel to look-direction are less visible as expected. However, certain lineaments even parallel to radar look-direction can still be detectable in a favorable topographic condition. Compared with TM image, the total number of detected lineaments in each direction in the SAR image increases or decreases ranging from 33% to 159% in length and from 28% to 187% in occurrence. The ratio of lineaments in SAR image to those in TM image with respect to direction can be fitted by a cosine function. The fitted function indicates that geological lineament is more easily detected in SAR image than in TM image within about $\pm$50$^{\circ}$ normal to radar look-direction. And lineaments with limited extension appear to be more sensitive to the look direction bias effect.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1555-1565
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• 2018

Detection of subtle ground deformation of volcanoes plays an important role in evaluating the risk and possibility of volcanic eruptions. Ground-fixed observation equipment is difficult to maintain and cost-inefficient. In contrast, satellite remote sensing can regularly monitor at low cost. In this paper, following the study of Chadwick et al. (2006), which applied the interferometric SAR (InSAR) technique to the Sierra Negra volcano, Galapagos. In order to investigate the deformation of the volcano before 2005 eruption, the recent activities of this volcano were analyzed using Sentinel-1, the latest SAR satellite. We obtained the descending mode Sentinel-1A SAR data from January 2017 to January 2018, applied the Persistent Scatter InSAR, and estimated the depth and expansion quantity of magma in recent years through the Mogi model. As a result, it was confirmed that the activity pattern of volcano prior to the eruption in June 2018 was similar to the pattern before the eruption in 2005 and was successful in estimating the depth and expansion amount. The results of this study suggest that satellite SAR can characterize the activity patterns of volcano and can be possibly used for early monitoring of volcanic eruption.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2000.10a
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• pp.1-15
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• 2000

Radar 영상은 능동적탐측기로서 밤과 낮의 구분없이 사용할 수 있고 또한 구름의 영향을 받지 않음으로 해서 여러 분야에서 사용되어왔다. 특히 SAR영상을 이용한 위상간섭법 (InSAR: Interferometric SAR)은 1990년대 초 미국의 JPL (Jet Propulsion Laboratory)에서 사용하기 시작하여 현재 원격탐측, 지구과학, 지구물리학, 측량학, 토목, 환경분야등에 다양하게 활용되고 있는 SAR영상을 이용한 최신의 원격탐측 기술이라 하겠다. 본 논문에서는 InSAR 방법을 중심으로 SAR 영상을 이용한 지형복원 방법과 변위관측 방법에 대해서 알아본다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.7
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• pp.580-583
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• 2017

To compensate the degraded SAR image due to the residual errors and the spatial variant errors remaining after the motion compensation in the airborne SAR, we have introduced the autofocus method based on the partition processing. Thus, after we perform the spatial partition for the spotlight SAR data and the time partition for the stripmap SAR data, we reconstruct the subpatch images for the partitioned data. Then, we perform the local autofocus with the suitability analysis process for the phase errors estimated by the autofocus. Moreover, if the estimated phase errors are not properly compensated for the subpatch images, we perform the phase compensation method with the weight to the estimated phase error close to the degraded subpatch image to increase the SAR image quality.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.46-54
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• 2015

SAR is a Radar to obtain the video information using a radio wave. Platform emit the radio wave, depending backscattered waves returned from the target object the signal to the distance, to create a topographical map is recorded in two-dimensional image. In this paper, through a simulation to apply a variety of window in the SAR image processing for SAR image recovery is to study the application effect of the window, as a result, at the side of the signal of the SNR, Flattop window to improve the best performance it was confirmed to show.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.17-26
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• 2016

This work proposes a 12b 60MS/s 0.18um CMOS Flash-SAR ADC for various systems such as wireless communications and portable video processing systems. The proposed Flash-SAR ADC alleviates the weakness of a conventional SAR ADC that the operation speed proportionally increases with a resolution by deciding upper 4bits first with a high-speed flash ADC before deciding lower 9bits with a low-power SAR ADC. The proposed ADC removes a sampling-time mismatch by using the C-R DAC in the SAR ADC as the combined sampling network instead of a T/H circuit which restricts a high speed operation. An interpolation technique implemented in the flash ADC halves the required number of pre-amplifiers, while a switched-bias power reduction scheme minimizes the power consumption of the flash ADC during the SAR operation. The TSPC based D-flip flop in the SAR logic for high-speed operation reduces the propagation delay by 55% and the required number of transistors by half compared to the conventional static D-flip flop. The prototype ADC in a 0.18um CMOS demonstrates a measured DNL and INL within 1.33LSB and 1.90LSB, with a maximum SNDR and SFDR of 58.27dB and 69.29dB at 60MS/s, respectively. The ADC occupies an active die area of $0.54mm^2$ and consumes 5.4mW at a 1.8V supply.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.847-859
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• 2021

Recently, as the number of high-resolution satellite SAR images increases, the demand for precise matching of SAR imagesin change detection and image fusion is consistently increasing. RMSE (Root Mean Square Error) values using GCPs (Ground Control Points) selected by analysts have been widely used for quantitative evaluation of image registration results, while it is difficult to find an approach for automatically measuring the registration accuracy. In this study, a feasibility analysis was conducted on using the FSIM (Feature Similarity) index as a measure to evaluate the registration accuracy. TerraSAR-X (TSX) staring spotlight data collected from various incidence angles and orbit directions were used for the analysis. FSIM was almost independent on the spatial resolution of the SAR image. Using a single SAR image, the FSIM with respect to registration errors was analyzed, then use it to compare with the value estimated from TSX data with different imaging geometry. FSIM index slightly decreased due to the differencesin imaging geometry such as different look angles, different orbit tracks. As the result of analyzing the FSIM value by land cover type, the change in the FSIM index according to the co-registration error was most evident in the urban area. Therefore, the FSIM index calculated in the urban was mostsuitable for determining the accuracy of image registration. It islikely that the FSIM index has sufficient potential to be used as an index for the co-registration accuracy of SAR image.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.737-746
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• 2022

Utilizing weather independent SAR images along with machine learning based object detector is effective in robust vessel monitoring. While conventional SAR images often applied amplitude data from Single Look Complex, exploitation of polarimetric parameters acquired from multiple polarimetric SAR images was yet to be implemented to vessel detection utilizing machine learning. Hence, this study used four polarimetric parameters (H, p₁, DoP, DPRVI) retrieved from eigen-decomposition and two backscattering coefficients (γ₀, _VV, γ₀, _VH) from radiometric calibration; six bands in total were respectively exploited from 52 Sentinel-1 SAR images, accompanied by vessel training data extracted from AIS information which corresponds to acquisition time span of the SAR image. Evaluating different cases of combination, the use of polarimetric indexes along with amplitude values derived enhanced vessel detection performances than that of utilizing amplitude values exclusively.