• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.5B
• /
• pp.260-267
• /
• 2008

As pervious the SAR(Security Aware Routing)[10] protocol is an secure Ad Hoc network protocol that finds a secure path, it is the security routing protocol that uses the security level of nodes as the routing information. However, the SAR protocol sometimes transfers data through inefficient transmission paths because it always tries to find secure nodes for a safe transmission. Since it is a protocol based on AODV[6], it will cause transmission delay as researching of security routing path. when a node is out of the data transmission range as its battery dying or movement. Although it is possible to connection of nodes because a characteristic of the SAR protocol, the connection is not easy to reconnect when the security level of intermediate node is lower than the level requested by a source node. In this paper, we suggest the MP-SAR based on the SAR to solve the SAR protocol's problem. The MP-SAR seeks multiple secure path for maintenance of data confidentiality using the expanded secure path detection techniques based on the SAR. It can transfer data quickly and reliably by using the shortest efficient path among multiple paths. In the research result, we proved a outstanding performance of MP-SAR than the previous SAR through comparison and analysis.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.148-148
• /
• 2017

본 연구에서는 합성개구레이더(Synthetic Aperture Radar, SAR) 인공위성 영상을 활용한 풍수해 피해지역 감지 기법을 제안하고자 한다. SAR 인공위성 자료를 분석하여 풍수해 피해 중 지반의 변화량 및 변화양상 감지를 분석하였다. 연구지역은 울릉도 전역이며, 2016년 8월 30일 제 10호 태풍 라이언록에 의한 피해를 분석하였다. SAR Interferometry(InSAR) 기법을 적용하여 홍수 전, 후의 지반 변화량을 분석하였다. 분석결과의 정확도를 파악하기 위해 분석결과를 실제 피해사례 및 피해 사진 등과 비교, 분석하여 검증을 실시하였다. 검증결과, 정성적인 지반변화 및 변화양상은 판별되었으나, 정량적인 지반변화량 파악은 어려운 것으로 나타났다. 현재 국내지역에 대해 InSAR 기법을 적용하여 홍수 전, 후의 지반변화 감지를 적용해본 사례가 많지 않은 실정이며, 본 연구는 국내지역에 대해 InSAR 기법을 적용하여 풍수해 피해감지를 하였다는 의미가 있다.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.590-593
• /
• 2004

Extraction of ocean surface current velocity offers important physical oceanographic parameters especially on understanding ocean environment. Although Remote Sensing techniques were highly developed, the investigation of ocean surface current using Synthetic Aperture Radar (SAR) is not an easy task. This paper presents the results of ocean surface current observation using Doppler Centroid of ERS-1 SAR data obtained off the coast of Korea peninsula. We employed the concept, in which Doppler frequency shift and the ocean surface current are closely related, to evaluate ocean surface current. Moving targets cause Doppler frequency shift of the back scattered radar waves of SAR, thus the line-of-sight velocity component of the scatters can be evaluated. The Doppler frequency shift can be measured by estimating the difference between Doppler Centroid of raw SAR data and reference Doppler Centroid. Theoretically, the Doppler Centroid is zero; however, squinted antenna which is affected by several physical factors causes Doppler Centroid to be nonzero. The reference Doppler Centroid can be obtained from measurements of sensor trajectory, attitude and Earth model. The estimated Doppler Centroid was compensated by considering the accurate attitude estimation of ERS-1 SAR. We could verify the correspondence between the estimated ocean surface current and observed in-situ data in the error bound.

• Proceedings of the IEEK Conference
• /
• 2000.11a
• /
• pp.505-508
• /
• 2000

The success of target reconstruction in SAR(Synthetic Aperture Radar) imaging system is greatly dependent on the coherent detection. Primary causes of incoherent detection are uncompensated target or sensor motion, random turbulence in propagation media, wrong path in radar platform, and etc. And these appear as multiplicative phase error to the echoed signal, which consequently, causes fatal degradations such as fading or dislocation of target image. In this paper, we present iterative phase error estimation scheme which uses echoed data in all temporal frequencies. We started with analyzing wave equation for one point target and extend to overall echoed data from the target scene - The two wave equations governing the SAR signal at two temporal frequencies of the radar signal are combined to derive a method to reconstruct the complex phase error function. Eventually, this operation attains phase error correction algorithm from the total received SAR signal. We verify the success of the proposed algorithm by applying it to the simulated spotlight-mode SAR data.

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

• Korean Journal of Remote Sensing
• /
• v.21 no.2
• /
• pp.145-162
• /
• 2005

To improve the accuracy of land-cover discrimination in SAB data classification, this paper presents a methodology that includes feature extraction and fusion steps with multi-temporal SAR data. Three features including average backscattering coefficient, temporal variability and coherence are extracted from multi-temporal SAR data by considering the temporal behaviors of backscattering characteristics of SAR sensors. Dempster-Shafer theory of evidence(D-S theory) and fuzzy logic are applied to effectively integrate those features. Especially, a feature-driven heuristic approach to mass function assignment in D-S theory is applied and various fuzzy combination operators are tested in fuzzy logic fusion. As experimental results on a multi-temporal Radarsat-1 data set, the features considered in this paper could provide complementary information and thus effectively discriminated water, paddy and urban areas. However, it was difficult to discriminate forest and dry fields. From an information fusion methodological point of view, the D-S theory and fuzzy combination operators except the fuzzy Max and Algebraic Sum operators showed similar land-cover accuracy statistics.

• Proceedings of the KSRS Conference
• /
• 1998.09a
• /
• pp.128-133
• /
• 1998

To assess the flood damages and to provide necessary information for preventing future catastrophe, it is necessary to appraise the 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 southern part of Korea. JERS L-band SAR data obtained during the summer of 1997 were used to delineate the inundated areas. In addition, Landsat TM data were also used for analyzing the land cover condition before the flooding. Once the two data sets were co-registered, each data was separately classified. The water surface areas extracted from the SAR data and the land cover map generated using the TM data were overlaid to determine the flood inundated areas. Although manual interpretation of water surfaces from the SAR image seems rather simple, the computer classification of water body requires clear understanding of radar backscattering behavior on the earth's surfaces. It was found that some surface features, such as rice fields, runaway, and tidal flat, have very similar radar backscatter to water surface. Even though satellite SAR data have a great advantage over optical remote sensor data for obtaining imagery on time and would provide valuable information to analyze flood, it should be cautious to separate the exact areas of flood inundation from the similar features.

• Korean Journal of Remote Sensing
• /
• v.24 no.4
• /
• pp.299-307
• /
• 2008

It is possible to extract qualified ground control points (GCPs) from SAR data itself without published maps. TerraSAR-X data that are one of highest spatial resolution among civilian SAR systems is now available. In this study, a sophisticated method for GCP extraction from TerraSAR-X data was tested and the quality of the extracted GCPs was evaluated. Mean values of the distance errors were 0.11m and -3.96 m with standard deviations of 6.52 m and 5.11 m in easting and northing, respectively. The result is one of the best among GCPs possibly extracted from any civilian remote sensing systems. The extracted GCPs were used for geo-rectification of IKONOS image. The method used in this study can be applied to KOMPSAT-5 for geo-rectification of high-resolution optic images acquired by KOMPSAT-2 or follow-up missions.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_2
• /
• pp.737-746
• /
• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.6_1
• /
• pp.519-528
• /
• 2012

It was pointed out that the terrain distortion of SAR image is even worse than that of optical image although SAR imagery has the advantages of being independent of solar illumination and weather conditions. It is thus necessary to correct terrain distortion in SAR image for various application areas to integrate SAR and optical image information. There has to be a clear evaluation of terrain correction of high resolution SAR image according to the quality of DEM because the DEM of study site is generally used in the process of terrain correction. To achieve this issue, this paper compared the effects of quality of Digital Elevation Model(DEM) in the process of terrain correction of high resolution SAR images, using the DEM produced from 1:5000 topographic contour maps, LiDAR DEM, ASTER GDEM, SRTM DEM. We used TerraSAR-X and Cosmo-SkyMed, as the test data set, which are constructed on the same X-band SAR system as KOMPSAT-5. In order to evaluate quantitatively the correction results, we conducted comparative evaluation with the KOMPSAT-2 ortho image of the same region. The evaluation results showed that the DEM produced from 1:5000 topographic contour maps achieved successful results in the terrain correction of SAR image compared with the other DEM data, and the widely used SRTM DEM data in various applications was not suitable for the terrain correction of high resolution SAR images.