• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.397-400
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• 2004

Synthetic Aperture Radar(SAR) is an active micro­wave instrument that performs high-resolution observation under almost all weather conditions. Although there are many advantages of SAR instrument, many complicated steps are involved in order to generate SAR image products. Many research and algorithms have been proposed to process radar signal and to increase the quality of SAR products. However, it is hard to find research which compare the quality of SAR products generated with different algorithms and processing methods. In our previous research, a SAR processing s/w was developed for a ground station. In addition, quality assessment procedures and their test parameters inside a SAR processor was proposed. The purpose of this paper is to evaluate the quality of SAR images generated from the developed SAR processing s/w. However, If there are no direct measurements such as radar reflector or scattering field measurement values it is difficult to compare SAR images generated with different methods. An alternative procedures and parameters for SAR image quality evaluation are presented and the problems involved in the comparison methods are discussed. Experiments based on real data have been conducted to evaluate and analyze quality of SAR images.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.729-732
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• 2005

This paper describes a time-spatial domain model for simulating raw data acquisition of space-borne SAR system. The position, velocity and attitude information of the platform at a certain time instance is used for deriving sensor-target model. Ground target is modelled by a set of point scatters with reflectivity and two-dimensional ground coordinates. The signal received by SAR is calculated for each slow and fast time instance by integrating the reflectivity and phase values from all target point scatters. Different from frequency domain simulation algorithms, the proposed time domain algorithm can provide fully physical modelling of SAR raw data simulation without any assumptions or approximations.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.332-335
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• 2008

Newly developing SAR (Synthetic Aperture Radar) sensors commonly include high resolution X-band those data are expected to contribute various applications. Recent few studies are presenting potential of X-band SAR data in forest related application. This study tried to investigate the relationship between forest stand parameters and multi-band SAR normalized backscattering. Multi-band SAR data was radiometric corrected to compare signal from different forest stand condition. Then correlation coefficients were estimated between attribute of forest stand map and normalized backscattering coefficients. Although overall correlation coefficients are not high, only X-band shows strong relationship with DBH class than other bands. The signal of C- and L-band is composed of a large number of discrete tree components such as leaves, stems, even background soil. In forest, strength of radar backscattering is affected by complex parameters. Further study might be considered more various forest stand parameters such as canopy density, stand height, volume, and biomass.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.442-447
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• 2002

When a SAR system operates in a full-polarimetic mode, the amount of the information one can extract is so complex that the effective presentation of the information is important. However, the information acquired from the polarimetric SAR data is often difficult to interpret by itself, because it is consisted of both the amplitude information and the phase information. Polarimetric parameters are the good way of representing the polarimetric SAR information in a quantitative manner. Also they can characterize the scattering behavior of the ground scatterer. In this research, extraction of polarimetric parameters, evaluation and interpretation of the scattering behavior of the ground with respect to polarimetric SAR signal are carried out. Using the NASA/JPL AIRSAR data, we estimated the polarimetric parameters and compared them in terms of the ground features. In general, extracted parameters well represent the characteristics of the different features on the ground.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.3
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• pp.117-124
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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 for the real-time data transmission of the massive SAR data in a limited time of mission. In this paper, based on the data link 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. The designed data link module can be effectively used for the spaceborne and airborne applications which requires to expand the high speed data link capability.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.161-170
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• 1994

The JERS-1 is an Earth Resources Satellite launched by NASDA (Natinal Space Development Agency) of Japan, in February in 1992 and has two sensors; SAR(L-Band Synthetic Aperture Radar) and OPS (SWIR and VNIR radiometers). In this research note, the basic properties and data characteristics of the SAR data are summarized based on the observations made on the data sets received for the Nahanni Canadian test site, Northwest Territories. The JERS-1 SAR data quality. including the spatial resolution of the data, is, in general, excellent for most geological applications.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.9
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• pp.723-732
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• 2017

Simplified factorizing-technique to improve the efficiency on computational procedure and the complexity of the conventional back-projection algorithm, which is used to reconstruct airborne FMCW-SAR image, is suggested, and the reconstruction process of SAR image by this simplified factorizing-technique are presented in this paper. This technique can be efficiently applied to airborne FMCW-SAR having a relatively narrow beamwidth and long synthetic aperture length, and its basic rationale is to exclude the data that has low level of contribution during computational procedure. Using the raw data of practical airborne FMCW-SAR system, performances of this proposed technique such as SAR image quality and processing time were compared and analyzed.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.205-214
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• 2015

In this study, a novel land-cover classification framework for multi-temporal SAR data is presented that can combine multiple features extracted through data transforms and multiple classifiers. At first, data transforms using principle component analysis (PCA) and 3D wavelet transform are applied to multi-temporal SAR dataset for extracting new features which were different from original dataset. Then, three different classifiers including maximum likelihood classifier (MLC), neural network (NN) and support vector machine (SVM) are applied to three different dataset including data transform based features and original backscattering coefficients, and as a result, the diverse preliminary classification results are generated. These results are combined via a majority voting rule to generate a final classification result. From an experiment with a multi-temporal ENVISAT ASAR dataset, every preliminary classification result showed very different classification accuracy according to the used feature and classifier. The final classification result combining nine preliminary classification results showed the best classification accuracy because each preliminary classification result provided complementary information on land-covers. The improvement of classification accuracy in this study was mainly attributed to the diversity from combining not only different features based on data transforms, but also different classifiers. Therefore, the land-cover classification framework presented in this study would be effectively applied to the classification of multi-temporal SAR data and also be extended to multi-sensor remote sensing data fusion.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.219-226
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• 2004

We measure subsidences occurred in a reclaimed coastal land, Noksan industrial complex, by using JERS-1 SAR (1996-1998) and RADARSAT-1 SAR (2002-2003) dataset. SAR with a high spatial resolution (about several or several tens meter) can reveal the two-dimensional distribution of settlement that would be bardly estimated from in situ measurements. The DInSAR results show significant deformation signal associated with soil consolidation. Accuracy of the settlements estimated by 2-pass differential interferometry (DInSAR) is evaluated using the measurements of settlement gauge. A two-dimensional subsidence map is constructed from 7 qualified pairs. Comparing the JERS-1 radar measurements with the ground truth data yields the correlation coefficient of 0.87 (RMSE of 1.44 cm). The regression line shows the gradient of 1.04 and intercepts close to the origin, which implies that the unbiased settlement can be measured by DInSAR technique. The residual settlements are also detected from RADARSAT-1 pairs. The extent and amount of the settlements are matched well with ground truth data.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.531-546
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• 2009

The main objective of this study is to analyse the polarimetric characteristics of the various terrain targets by ground-based polarimetric SAR system and to confirm the compatible and effective polarimetric analysis method to reveal the polarization properties of different terrain targets by the GB-SAR. The fully polarimetric GB-SAR data with HH, HV, VH, and VV components were focused using the Deramp-FFT (DF) algorithm. The focused GB-SAR images were processed by the H/A/$\alpha$ polarimetric decomposition and the combined H/$\alpha$ or H/A/$\alpha$ and Wishart classification method. The segmented image and distribution graphs in H/$\alpha$ plane using Cloude and Pottier's method showed a reliable result that this quad-polarization GB-SAR data could be useful to classified corresponding scattering mechanism. The H/$\alpha$-Wishart and H/A/$\alpha$-Wishart classification results showed that a natural media and an artificial target were discriminated by the combined classification, in particular, after applying multi-looking and the Lee refined speckle filter.