• Title/Summary/Keyword: SAR Data

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Digital Elevation Map Generation using SAR Stereo Technique with Radarsat Images over Seoul Area

  • Ka, Min-Ho;Kim, Man-Jo
    • Korean Journal of Remote Sensing
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    • v.17 no.2
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    • pp.155-164
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    • 2001
  • In this study, we describe the technique for deriving a digital elevation model (DEM) from a synthetic aperture radar (SAR) stereo image pair and apply it to an image pair over "Kwanak-san" in Seoul, Korea. This paper contains brief discussion of the use of stereo SAR to derive topographic data, description of the overall structure of the stereo SAR processing system, description of the site and SAR data used for the evaluation and the source of validation data, results of the stereo SAR processing, analysis and evaluation of their accuracy against map data, and finally summarizes the main highlights of the method used, comments and recommendations on its future implementation.

Requirements of processing parameters for Multi-Satellites SAR Data Focusing Software

  • Kwak Sunghee;Kim Kwang Yong;Lee Young-Ran;Shin Dongseok;Jeong Soo;Kim Kyung-Ok
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.401-404
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    • 2004
  • SAR (Synthetic Aperture Radar) signal data need a focusing procedure to make the information available to the user. In recent SAR systems, various sensing modes and mission operations are applied to acquire high-resolution SAR images. Therefore, in order to develop generalized focusing software for multi-satellites, a regularized parameter configuration that sufficiently represents sensor and platform characteristics of the SAR system is required. The objective of this paper is to introduce the consideration of parameter definition for developing a generalized SAR processor and to discuss the flexibility and extensibility of defined parameters. The proposed parameter configuration can be applied to a SAR processor. Experiments based on real data will show the suitability of the suggested processing parameters.

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An Optimization Method for BAQ(Block Adaptive Quantization) Threshold Table Using Real SAR Raw Data (영상레이다 원시데이터를 이용한 BAQ(Block Adaptive Quantization) 최적화 방법)

  • Lim, Sungjae;Lee, Hyonik;Kim, Seyoung;Nam, Changho
    • Journal of the Korea Institute of Military Science and Technology
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    • v.20 no.2
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    • pp.187-196
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    • 2017
  • The size of raw data has dramatically increased due to the recent trend of Synthetic Aperture Radar(SAR) development plans for high resolution and high definition image acquisition. The large raw data has an impact on satellite operability due to the limitations of storage and transmission capacity. To improve the SAR operability, the SAR raw data shall be compressed before transmission to the ground station. The Block Adaptive Quantization (BAQ) algorithm is one of the data compression algorithm and has been used for a long time in the spaceborne SAR system. In this paper, an optimization method of BAQ threshold table is introduced using real SAR raw data to prevent the degradation of signal quality caused by data compression. In this manner, a new variation estimation strategy and a new threshold method for block type decision are introduced.

Study on the Requirement, Consideration, and Critical Baseline in SAR Design Process for the IFSAR Technique (IFSAR 기법 활용을 위해 SAR 설계시 요구조건, 고려사항 및 최대 베이스라인 연구)

  • 홍인표;박한규
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.11A
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    • pp.1858-1863
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    • 2001
  • SAR data consist of magnitude and phase, and IFSAR technique using phase data is very useful high technology Producing fee height information. To use IFSAR technique effectively in the operation of SAR, this paper suggests the essential requirement and main consideration during SAR design process. Also the critical baseline, one of the principal elements, is derived, and it proposes applicable method through the simulation and discussion to the E-SAR.

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A FREQUENCY DOMAIN RAW SIGNAL SIMULATOR FOR SAR

  • Kwak Sunghee;Kim Moon-Gyu;Shin Dongseok;Shin Jae-Min
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.530-533
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    • 2005
  • A raw signal simulator for synthetic aperture radar (SAR) is a useful tool for the design and implementation of SAR system. Also, in order to analyze and verify the developed SAR processor, the raw signal simulator is required. Moreover, there is the need for a test system to help designing new SAR sensors and mission of SAR system. The derived parameters of the SAR simulator also help to generate accurate SAR processing algorithms. Although the ultimate purpose of this research is to presents a general purpose SAR simulator, this paper presents a SAR simulator in frequency domain at the first step. The proposed simulator generates the raw signal by changing various simulation parameters such as antenna parameters, modulation parameters, and sampling parameters. It also uses the statistics from an actual SAR image to imitate actual physical scattering. This paper introduces the procedures and parameters of the simulator, and presents the simulation results. Experiments have been conducted by comparing the simulated raw data with original raw SAR image. In addition, the simulated raw data have been verified through commercial SAR processing software.

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REQUIREMENT AND INITIALIZATION OF KOMPSAT-5 CALIBRATION AND VALIDATION

  • Lee, Dong-Han;Seo, Doo-Chun;Song, Jeong-Heon;Park, Soo-Young;Lim, Hyo-Suk
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.776-779
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    • 2006
  • KOMPSAT-5 that will be launched at the end of 2008 has a SAR (Synthetic Aperture Radar) payload. Since the Calibration and Validation of a satellite SAR is different from a passive optical camera as KOMPSAT-2 MSC and KOMPSAT-3 payload, we have started from the basis of SAR system. Firstly, the general SAR Cal/Val parameters have been gathered and defined. Secondly, we have been choosing the Cal/Val parameters suitable to KOMPSAT-5. Thirdly, the methods of SAR Cal/Val with the parameters have been studied. Fourthly, the requirement of Cal/Val devices and Cal/Val site has been studied.

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Regional Scale Rice Yield Estimation by Using a Time-series of RADARSAT ScanSAR Images

  • Li, Yan;Liao, Qifang;Liao, Shengdong;Chi, Guobin;Peng, Shaolin
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.917-919
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    • 2003
  • This paper demonstrates that RADARSAT ScanSAR data can be an important data source of radar remote sensing for monitoring crop systems and estimation of rice yield for large areas in tropic and sub-tropical regions. Experiments were carried out to show the effectiveness of RADARSAT ScanSAR data for rice yield estimation in whole province of Guangdong, South China. A methodology was developed to deal with a series of issues in extracting rice information from the ScanSAR data, such as topographic influences, levels of agro-management, irregular distribution of paddy fields and different rice cropping systems. A model was provided for rice yield estimation based on the relationship between the backscatter coefficient of multi-temporal SAR data and the biomass of rice.

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Spaceborne High Speed Data Link Design for Multi-Mode SAR Image Data Transmission

  • Kwag, Young-Kil
    • Journal of electromagnetic engineering and science
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    • v.2 no.1
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    • pp.39-44
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    • 2002
  • A high speed data link capability is one of the critical factors in determining the performance of the spaceborne SAR system with high resolution because of the strict requirement far the real-time data transmission of the massive SAR data in a limited time of mission. In this paper, based on the data lint model characterized by the spaceborne small SAR system, the high rate multi-channel data link module is designed including link storage, link processor, transmitter, and wide-angle antenna. The design results are presented with the performance analysis on the data link budget as well as the multi-mode data rate in association with the SAR imaging mode of operation from high resolution to the wide swath.

Topographic Normalization of Satellite Synthetic Aperture Radar(SAR) Imagery (인공위성 레이더(SAR) 영상자료에 있어서 지형효과 저감을 위한 방사보정)

  • 이규성
    • Korean Journal of Remote Sensing
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    • v.13 no.1
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    • pp.57-73
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    • 1997
  • This paper is related to the correction of radiometric distortions induced by topographic relief. RADARSAT SAR image data were obtained over the mountainous area near southern part of Seoul. Initially, the SAR data was geometrically corrected and registered to plane rectangular coordinates so that each pixel of the SAR image has known topographic parameters. The topographic parameters (slope and aspect) at each pixel position were calculated from the digital elevation model (DEM) data having a comparable spatial resolution with the SAR data. Local incidence angle between the incoming microwave and the surface normal to terrain slope was selected as a primary geometric factor to analyze and to correct the radiometric distortions. Using digital maps of forest stands, several fields of rather homogeneous forest stands were delineated over the SAR image. Once the effects of local incidence angle on the radar backscatter were defined, the radiometric correction was performed by an empirical fuction that was derived from the relationship between the geometric parameters and mean radar backscatter. The correction effects were examined by ground truth data.

Deep-learning based SAR Ship Detection with Generative Data Augmentation (영상 생성적 데이터 증강을 이용한 딥러닝 기반 SAR 영상 선박 탐지)

  • Kwon, Hyeongjun;Jeong, Somi;Kim, SungTai;Lee, Jaeseok;Sohn, Kwanghoon
    • Journal of Korea Multimedia Society
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    • v.25 no.1
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    • pp.1-9
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    • 2022
  • Ship detection in synthetic aperture radar (SAR) images is an important application in marine monitoring for the military and civilian domains. Over the past decade, object detection has achieved significant progress with the development of convolutional neural networks (CNNs) and lot of labeled databases. However, due to difficulty in collecting and labeling SAR images, it is still a challenging task to solve SAR ship detection CNNs. To overcome the problem, some methods have employed conventional data augmentation techniques such as flipping, cropping, and affine transformation, but it is insufficient to achieve robust performance to handle a wide variety of types of ships. In this paper, we present a novel and effective approach for deep SAR ship detection, that exploits label-rich Electro-Optical (EO) images. The proposed method consists of two components: a data augmentation network and a ship detection network. First, we train the data augmentation network based on conditional generative adversarial network (cGAN), which aims to generate additional SAR images from EO images. Since it is trained using unpaired EO and SAR images, we impose the cycle-consistency loss to preserve the structural information while translating the characteristics of the images. After training the data augmentation network, we leverage the augmented dataset constituted with real and translated SAR images to train the ship detection network. The experimental results include qualitative evaluation of the translated SAR images and the comparison of detection performance of the networks, trained with non-augmented and augmented dataset, which demonstrates the effectiveness of the proposed framework.