• 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 Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.128-129
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• 2010

기존의 고도계는 레이더 특성에 의해 직하부의 높이 값을 정밀하게 관측할 수 없었다. 그러나 레이더 간섭 고도계는 SAR(Synthetic Aperture Radar) 영상의 칩 펄스(Chirp Pulse)를 이용한 고정밀 경사거리(Slant Range Distance)관측, 도플러 효과를 이용한 고정밀 경사각(Squint Angle)의 관측 및 레이더 간섭기법(SAR Interferometry)을 이용한 고정밀 관측각(Look Angle)의 관측을 가능하게 하였다. 이 연구의 목적은 레이더 간섭 고도계의 효율적인 신호처리 기법의 개발에 있다.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.266-269
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• 2007

This paper reports the preliminary results on the study of radargrammetry especially for a high-resolution satellite synthetic aperture radar system. Theoretical configurations for radargrammetry in terms of coverage, orbit selection, incidence angles, height sensitivity of parallax and height resolution of DEM were calculated according to the proposed orbit characteristics and the imaging modes of KOMPSAT-5 SAR. Possible imaging strategies and mission scenarios for coverage versus rapidity are suggested for a future mission dedicated to radargrammetry.

• Korean Journal of Remote Sensing
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• v.21 no.1
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• pp.59-72
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• 2005

Interferometric synthetic aperture radar (InSAR) is a remote sensing technique capable of measuring ground surface deformation with sub-centimeter precision and spatial resolution in tens-of­meters over a large region. This paper describes basics of InSAR and highlights our studies of Alaskan volcanoes with InSAR images acquired from European ERS-l and ERS-2, Canadian Radarsat-l, and Japanese JERS-l satellites.

• Current Industrial and Technological Trends in Aerospace
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• v.8 no.2
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• pp.98-104
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• 2010

The demand for Satellite Images is continuously increasing owing to the various applications of optical satellite images. However, the acquisition of optical images has a limitation due to problems of weather and day & night. because an optical satellite makes images with reflections of sunlight. Therefore, SAR Satellite, which uses electromagnetic waves to make an image, gives increased demand to various applications. It also makes increased interest. In this paper, a calibration and validation system, which is an essential element for high quality Radar images, is studied.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.28-28
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• 2022

본 연구는 용담댐유역을 포함한 금강 유역 상류 지역을 대상으로 Sentinel-1 SAR (Synthetic Aperture Radar) 위성영상을 기반으로 한 토양수분 산정을 목적으로 하였다. Sentinel-1 영상은 2019년에 대해 12일 간격으로 수집하였고, 영상의 전처리는 SNAP (SentiNel Application Platform)을 활용하여 기하 보정, 방사 보정 및 Speckle 보정을 수행하여 VH (Vertical transmit-Horizontal receive) 및 VV (Vertical transmit-Vertical receive) 편파 후방산란계수로 변환하였다. 토양수분 산정에는 Water Cloud Model (WCM)이 활용되었으며, 모형의 식생 서술자(Vegetation descriptor)는 RVI (Radar Vegetation Index)와 NDVI (Normalized Difference Vegetation Index)를 활용하였다. RVI는 Sentinel-1 영상의 VH 및 VV 편파자료를 이용해 산정하였으며, NDVI는 동기간에 대해 10일 간격으로 수집된 Sentinel-2 MSI (MultiSpectral Instrument) 위성영상을 활용하여 산정하였다. WCM의 검정 및 보정은 한국수자원공사에서 제공하는 10 cm 깊이의 TDR (Time Domain Reflectometry) 센서에서 실측된 6개 지점의 토양수분 자료를 수집하여 수행하였으며, 매개변수의 최적화는 비선형 최소제곱(Non-linear least square) 및 PSO (Particle Swarm Optimization) 알고리즘을 활용하였다. WCM을 통해 산정된 토양수분은 피어슨 상관계수(Pearson's correlation coefficient)와 평균제곱근오차(Root mean square error)를 활용하여 검증을 수행할 예정이다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.1
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• pp.49-60
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• 2012

Synthetic aperture radar (SAR) has been employed in various fields due to its capability to generate high resolution images regardless of weather and visibility. This paper presents a performance analysis on the image formation of high resolution SAR according to various slant range distance and synthetic aperture lengths using a range migration algorithm simulator. Although the visual performance on the SAR image is more accurate, a numeric analysis resulted in a comparable measurement. More specifically, raw data were generated for an ideal point target upon imaging geometries and design parameters such as slant range distance and synthetic aperture lengths. Finally, spatial resolution, peak to sidelobe ratio and integrated sidelobe ratio are drawn to provide SAR capabilities in the initial concept design, final in-flight calibration and validation stages.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.2
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• pp.164-169
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• 2010

Since the range and Doppler resolution of the synthetic aperture radar(SAR) image becomes very high, the target detection accuracy can be significantly increased, but the computational burden is also increased. The conventional single-cell based CFAR detector performs the target detection on every single cell basis, thus it causes the serious increment of the computational load. In this paper, the improved two-step MCA-CFAR detector is proposed for the improvement of the target detection as well as the reduction of computational load: the first step is to use the MCA-CFAR, and the second step is to use the single-cell based CFAR detection in the expected target area for final decision. The performance of the proposed algorithm is compared with the conventional single-cell based CFAR and MCA-CFAR on SAR images.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.163-171
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• 2005

I have developed a processor for synthetic aperture radar (SAR) raw data compression using range-doppler algorithm for educational purpose. The program realized a generic SAR focusing algorithm so that it can deal with any SAR system if the specification is known. It can run efficiently on a low-cost computer by selecting minimum size out of a whole dataset, and can produce intermediate images during the process. Especially, the program is designed for educational purpose in such a way that Doppler centroid and azimuth ambiguity can be determined graphically by the user. By distributing the source code and the algorithm to public, I intend to maximize the educational effect on understanding and utilizing SAR data. This paper introduces the principle of SAR focusing algorithm embedded on the eSAR processor and shows an example of data processing using ERS-1 raw data.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1589-1605
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• 2022

Phase unwrapping is an essential procedure for interferometric synthetic aperture radar techniques. Accordingly, a lot of phase unwrapping methods have been developed. Deep-learning-based unwrapping methods have recently been proposed. In this paper, we reviewed state-of-the-art deep-learning-based unwrapping approaches in terms of 1) the approaches to predicting unwrapped phases, 2) deep learning model structures for phase unwrapping, and 3) training data generation. The research trend of the approaches to predicting unwrapped phases was introduced by categorizing wrap count segmentation, phase jump classification, phase regression, and deep-learning-assisted method. We introduced the case studies of deep learning model structure for phase unwrapping, and model structure optimization to relate the overall phase information. In addition, we summarized the research trend of the training data generation approaches in the views of phase gradient and noise in the main. And the future direction in deep-learning-based phase unwrapping was presented. It is expected that this paper is used as guideline for exploring future direction of deep-learning-based phase unwrapping research in Korea.