• Title/Summary/Keyword: Synthetic aperture radar (SAR)

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A Review on Deep-learning-based Phase Unwrapping Technique for Synthetic Aperture Radar Interferometry (딥러닝 기반 레이더 간섭 위상 언래핑 기술 고찰)

  • Baek, Won-Kyung;Jung, Hyung-Sup
    • 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.

SAR(Synthetic Aperture Radar) 3-Dimensional Scatterers Point Cloud Target Model and Experiments on Bridge Area (영상레이더(SAR)용 3차원 산란점 점구름 표적모델의 교량 지역에 대한 적용)

  • Jong Hoo Park;Sang Chul Park
    • Journal of the Korea Society for Simulation
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    • v.32 no.3
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    • pp.1-8
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    • 2023
  • Modeling of artificial targets in Synthetic Aperture radar (SAR) mainly simulates radar signals reflected from the faces and edges of the 3D Computer Aided Design (CAD) model with a ray-tracing method, and modeling of the clutter on the Earth's surface uses a method of distinguishing types with similar distribution characteristics through statistical analysis of the SAR image itself. In this paper, man-made targets on the surface and background clutter on the terrain are integrated and made into a three-dimensional (3D) point cloud scatterer model, and SAR image were created through computational signal processing. The results of the SAR Stripmap image generation of the actual automobile based SAR radar system and the results analyzed using EM modeling or statistical distribution models are compared with this 3D point cloud scatterer model. The modeling target is selected as an bridge because it has the characteristic of having both water surface and ground terrain around the bridge and is also a target of great interest in both military and civilian use.

Assessment of Antarctic Ice Tongue Areas Using Sentinel-1 SAR on Google Earth Engine (Google Earth Engine의 Sentienl-1 SAR를 활용한 남극 빙설 면적 변화 모니터링)

  • Na-Mi Lee;Seung Hee Kim;Hyun-Cheol Kim
    • Korean Journal of Remote Sensing
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    • v.40 no.3
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    • pp.285-293
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    • 2024
  • This study explores the use of Sentinel-1 Synthetic Aperture Radar (SAR), processed through Google Earth Engine (GEE), to monitor changes in the areas of Antarctic ice shelves. Focusing on the Campbell Glacier Tongue (CGT) and Drygalski Ice Tongue (DIT),the research utilizes GEE's cloud computing capabilities to handle and analyze large datasets. The study employs Otsu's method for image binarization to distinguish ice shelves from the ocean and mitigates detection errors by averaging monthly images and extracting main regions. Results indicate that the CGT area decreased by approximately 26% from January 2016 to January 2024, primarily due to calving events,while DIT showed a slight increase overall,with notable reduction in recent years. Validation against Sentinel-2 optical images demonstrates high accuracy,underscoring the effectiveness of SAR and GEE for continuous, long-term monitoring of Antarctic ice shelves.

Investigation of Polarimetric SAR Remote Sensing for Landslide Detection Using PALSAR-2 Quad-pol Data

  • Cho, KeunHoo;Park, Sang-Eun;Cho, Jae-Hyoung;Moon, Hyoi;Han, Seung-hoon
    • Korean Journal of Remote Sensing
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    • v.34 no.4
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    • pp.591-600
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    • 2018
  • Recent SAR systems provide fully polarimetric SAR data, which is known to be useful in a variety of applications such as disaster monitoring, target recognition, and land cover classification. The objective of this study is to evaluate the performance of polarization SAR data for landslide detection. The detectability of different SAR parameters was investigated based on the supervised classification approach. The classifier used in this study is the Adaptive Boosting algorithms. A fully polarimetric L-band PALSAR-2 data was used to examine landslides caused by the 2016 Kumamoto earthquake in Kyushu, Japan. Experimental results show that fully polarimetric features from the target decomposition technique can provide improved detectability of landslide site with significant reduction of false alarms as compared with the single polarimetric observables.

WAVENUMBER CORRELATION ANALYSIS OF RADAR INTERFEROGRAM

  • Won, Joong-Sun;Kim, Jeong-Woo
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.425-428
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    • 1999
  • The radar interferogram represents phase differences between the two synthetic aperture radar observations acquired in slightly different angle. The success of the radar interferometric application largely depends on the quality of the interferogram generated from two or more synthetic aperture radar data sets. We propose here to apply the wavenumber correlation analysis to the in-phase and quadrature phase of the radar interferogram. The wavenumber correlation analysis is to resolve the highly correlated components from the low correlation components by estimating correlation coefficients for each wavenumber component. Through this approach, one can easily distinguish the signal components from the noise components in the wavenumber domain. Therefore, the wavenumber correlation analysis of the radar interferogram can be utilized to design post filter and to estimate the quality of interferogram. We have tested the wavenumber correlation analysis using a Radarsat SAR data pair to demonstrated the effectiveness of

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Analysis of Flood Inundated Area Using Multitemporal Satellite Synthetic Aperture Radar (SAR) Imagery (시계열 위성레이더 영상을 이용한 침수지 조사)

  • Lee, Gyu-Seong;Kim, Yang-Su;Lee, Seon-Il
    • Journal of Korea Water Resources Association
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    • v.33 no.4
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    • pp.427-435
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    • 2000
  • It is often crucial to obtain a map of flood inundated area with more accurate and rapid manner. This study attempts to evaluate the potential of satellite synthetic aperture radar (SAR) data for mapping of flood inundated area in Imjin river basin. Multitemporal RADARSAT SAR data of three different dates were obtained at the time of flooding on August 4 and before and after the flooding. Once the data sets were geometrically corrected and preprocessed, the temporal characteristics of relative radar backscattering were analyzed. By comparing the radar backscattering of several surface features, it was clear that the flooded rice paddy showed the distinctive temporal pattern of radar response. Flooded rice paddy showed significantly lower radar signal while the normally growing rice paddy show high radar returns, which also could be easily interpreted from the color composite imagery. In addition to delineating the flooded rice fields, the multitemporal radar imagery also allow us to distinguish the afterward condition of once-flooded rice field.

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COSMO-SkyMed 2 Image Color Mapping Using Random Forest Regression

  • Seo, Dae Kyo;Kim, Yong Hyun;Eo, Yang Dam;Park, Wan Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.4
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    • pp.319-326
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    • 2017
  • SAR (Synthetic aperture radar) images are less affected by the weather compared to optical images and can be obtained at any time of the day. Therefore, SAR images are being actively utilized for military applications and natural disasters. However, because SAR data are in grayscale, it is difficult to perform visual analysis and to decipher details. In this study, we propose a color mapping method using RF (random forest) regression for enhancing the visual decipherability of SAR images. COSMO-SkyMed 2 and WorldView-3 images were obtained for the same area and RF regression was used to establish color configurations for performing color mapping. The results were compared with image fusion, a traditional color mapping method. The UIQI (universal image quality index), the SSIM (structural similarity) index, and CC (correlation coefficients) were used to evaluate the image quality. The color-mapped image based on the RF regression had a significantly higher quality than the images derived from the other methods. From the experimental result, the use of color mapping based on the RF regression for SAR images was confirmed.

Generation of ISAR Image for Realistic Target Model Using General Purpose EM Simulators (범용 전자기파 시뮬레이터를 이용한 사실적 표적 모델에 대한 역합성 개구면 레이다 영상 합성)

  • Kim, Seok;Nikitin, Konstantin;Ka, Min-Ho
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.26 no.2
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    • pp.189-195
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    • 2015
  • There are many research works on the SAR image generation using EM(Electro Magnetic) simulation. Particularly, there are several dedicated S/Ws for SAR image generation and analysis. But, most of them are not available to the public due to the reason for defense and security. In this paper, we describe the generation of ISAR images for a realistic target model using the general purpose EM simulator like FEKO. This method can benefit us many advantages like building the database of many targets for target recognition with cost-and-time effective way.

A Study for Development Plan of SAR Core Technology Through Technology Readiness Level Survey and Analysis (기술 수준조사 및 분석을 통한 SAR(합성개구면 레이다) 핵심기술 개발방안 연구)

  • Kwak, Jun-Young;Jeong, Dae-Gwon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.4
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    • pp.655-662
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    • 2011
  • SAR(Synthetic Aperture Radar) has the ability to generate high resolution images regardless of a weather condition(e.g. visibility good or poor and day or night, etc.). SAR is considered as one of the most important powers and needs for the future since it has been utilized in a number of important military fields such as early warning, urban defense, missile guidance system, etc. Additionally there are many civilian demands and applications in aviation, traffic control, earth and space explorations, weather forecast etc. This days, the ability to acquire and analyze information is needed to cope with the urgency of global politics and international changes. In this paper, technical survey and development review for SAR systems are investigated to derive the core and immature technologies of domestic defense industry.

A Study on Parallel Performance Optimization Method for Acceleration of High Resolution SAR Image Processing (고해상도 SAR 영상처리 고속화를 위한 병렬 성능 최적화 기법 연구)

  • Lee, Kyu Beom;Kim, Gyu Bin;An, Sol Bo Reum;Cho, Jin Yeon;Lim, Byoung-Gyun;Kim, Dong-Hyun;Kim, Jeong Ho
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.46 no.6
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    • pp.503-512
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    • 2018
  • SAR(Synthetic Aperture Radar) is a technology to acquire images by processing signals obtained from radar, and there is an increasing demand for utilization of high-resolution SAR images. In this paper, for high-speed processing of high-resolution SAR image data, a study for SAR image processing algorithms to achieve optimal performance in multi-core based computer architecture is performed. The performance deterioration due to a large amount of input/output data for high resolution images is reduced by maximizing the memory utilization, and the parallelization ratio of the code is increased by using dynamic scheduling and nested parallelism of OpenMP. As a result, not only the total computation time is reduced, but also the upper bound of parallel performance is increased and the actual parallel performance on a multi-core system with 10 cores is improved by more than 8 times. The result of this study is expected to be used effectively in the development of high-resolution SAR image processing software for multi-core systems with large memory.