• Journal of Navigation and Port Research
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• v.31 no.1 s.117
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• pp.35-42
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• 2007

Recently satellite SAR techniques have become essential observation tools for various ocean phenomena such as wind, wave, and current. The CMOD4 and CMOD-IFR2 models are used to calculate the magnitude of wind at SAR resolution with no directional information. Combination of the wave-SAR spectrum analysis and the inter-look cross-spectra techniques provides amplitude and direction of the ocean wave over a square-km sized imagette, The Doppler shift measurement of SAR image yields surface speed of the ocean current along the radar looking direction, again at imagette resolution. In this paper we report the development of a SAR Ocean processor(SOP) incorporating all of these techniques. We have applied the SOP to several RADARSAT-1 images of the coast of Korean peninsula and compared the results with oceanographic data, which showed reliability of spaceborne SAR-based oceanographic research.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.448-453
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• 2002

Remote sensing technology is one of the most powerful tools for human to know the nature and their living environment. However, before microwave remote sensing was developed and applied, remote sensing application was limited strongly by weather and time. Microwave remote sensing technology solves the problem. It makes us to have the capability to acquire information at all time of the day and under all weather condition, and make remote sensing technology be used in more wider area. Microwave remote sensing system include mainly Synthetic Aperture Radar (SAR), Microwave Radiometer, Microwave Scatterometer, and Altimeter (ALT). As SAR can acquire image whose spatial resolution is similar with visible and infrared image, it is paying much attention to and playing a more and more important role in earth observation. In recent year, the development of new SAR technology (multi-band and multi-polarization technology, InSAR technology, D-InSAR technology, and so on) makes SAR remote sensing go to an new stage, and its application area become more and more widely. The first Synthetic Aperture Radar (SAR) in the world appeared in 1960. After that, SAR and its application all developed very fast. Some radar satellites launched and run (include Seasat-A in 1978, ERS-1 in 1991, JERS-1 in 1992, Radarsat in 1995, and so on) promote SAR research and application in world greatly. China began to develop its SAR sensor and research SAR application in 1970s. After more than 30 years' research, it get some important development in sensor development data processing method, and application. Some operational systems have been used and play an important role. This paper will introduce the development of SAR technology and its application in China.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.5
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• pp.366-374
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• 2018

In cases of airborne equipped with SAR, because the occurrence of motion is inevitable, it is necessary to apply autofocus techniques to SAR images to improve the image performance degradations caused by residual errors. Herein, a robust autofocus algorithm based on the minimum entropy criteria is proposed for the real SAR data in the spotlight mode. The convergence condition of the phase error estimation is checked at every iteration and if it is violated, the size of the phase error estimation is adjusted to the convergence condition. The real SAR raw data is used to demonstrate the excellent performance of the proposed algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1D
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• pp.89-94
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• 2012

The RFM (Rational Function Model), as an alternative to physical sensor models has been widely used for photogrammetric processing of high resolution optical satellite imagery. However, the application of RF modeling to the SAR (Synthetic Aperture Radar) is very limited. In this paper, stereo radargrammetric processing of TerraSAR-X stereo pairs with RFM is implemented and analyzed. The investigation has shown that the accuracy of TerraSAR-X DSM is similar to that of the commercial S/W product. Finally, it is demonstrated that RFM is effective and feasible in the application to the radargrammetric SAR image processing.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.422-425
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• 2008

TerraSAR-X is new radar satellite operated at X-band, multi polarization, and multi beam mode. Compared with C-band or L-band SAR, the X-band system inherently suffers from more temporal decorrelation, but is more sensitive to surface deformation monitoring due to short wavelength (3.1 cm) and high spatial resolution (1m-3m). It is generally expected that sensitivity to estimate surface movement using TerraSAR-X will be increased by the factor of 10, compared to current C-band system with low spatial resolution such as ERS-2, Envisat. Many urban areas are experiencing land subsidence due to water, oil and natural gas withdrawal, underground excavation, sediment compaction, and so on. Monitoring of surface deformation is valuable for effectively limiting damage areas. In addition high accuracy and spatially dense subsidence map can be achieved by X-band InSAR observation, promoting identification and separation of various subsidence processes and leading to enhanced understanding via mechanical modeling. In this study we will introduce some initial InSAR results using new TerraSAR-X SAR data for surface deformation monitoring.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.12
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• pp.1345-1351
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• 2007

This paper proposes a polarimetric SAR image classification technique based on the degree of poarization(DoP) and copolarized phase-difference(CPD) statistics. At first, the formulation for the DoP and CPD is derived. Then, the classification technique is verified with the SAR full polarimetric L-band data with consideration of exceptional cases. The technique has capability of classifying SAR data into four major classes, such as bare surface, short-vegetation canopy, tall-vegetation canopy, and village.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.49-62
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• 1994

Look direction bias in a single look SAR image can often be misinterpreted in the geological application of radar data. This paper investigates digital processing techniques for SAR image data integration and compensation of the SAR data look direction bias. The two important approaches for reducing look direction bias and integration of multiple SAR data sets are (1) principal component analysis (PCA), and (2) wavelet transform(WT) integration techniques. These two methods were investigated and tested with the ERS-1 (VV-polarization) and CCRS*s airborne (HH-polarization) C-SAR image data sets recorded over the Sudbury test site, Canada. The PCA technique has been very effective for integration of more than two layers of digital image data. When there only two sets of SAR data are available, the PCA thchnique requires at least one more set of auxiliary data for proper rendition of the fine surface features. The WT processing approach of SAR data integration utilizes the property which decomposes images into approximated image ( low frequencies) characterizing the spatially large and relatively distinct structures, and detailed image (high frequencies) in which the information on detailed fine structures are preserved. The test results with the ERS-1and CCRS*s C-SAR data indicate that the new WT approach is more efficient and robust in enhancibng the fine details of the multiple SAR images than the PCA approach.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.5
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• pp.462-475
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• 2022

Different from the field of electro-optical(EO) image analysis, there has been less interest in similarity metrics between synthetic aperture radar(SAR) target images. A reliable and objective similarity analysis for SAR target images is expected to enable the verification of the SAR measurement process or provide the guidelines of target CAD modeling that can be used for simulating realistic SAR target images. For this purpose, this paper presents a similarity analysis method based on the siamese network that quantifies the subjective assessment through the distance learning of similar and dissimilar SAR target image pairs. The proposed method is applied to MSTAR SAR target images of slightly different depression angles and the resultant metrics are compared and analyzed with qualitative evaluation. Since the image similarity is somewhat related to recognition performance, the capacity of the proposed method for target recognition is further checked experimentally with the confusion matrix.