• Proceedings of the Korea Electromagnetic Engineering Society Conference
• /
• 2000.11a
• /
• pp.29-33
• /
• 2000

The classical image reconstruction for stripmap SAR is based on the Fresnel approximation which utilizes deramping or chirp deconvolution in the synthetic aperture(slow-time) domain. Another approach in formulating stripmap SAR processing and imaging is based on the SAR wavefront reconsturction theory, and analysis of the SAR signal in the slow-time via the spherical wave Fourier decomposition of the radar radiation pattern. In this paper, we compare the Fresnel approximation and the wavefrong reconstruction methods using simulated stripmap SAR dada.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.21 no.9
• /
• pp.955-964
• /
• 2010

In this paper, a compensation method of the amplitude and phase errors from the T/R(Transmit/Receive) modules in an active SAR(Synthetic Aperture Radar) system is introduced. The errors are defined and classified, and characterized by analyzing the measurement data acquired from the pilot test. To compensate these errors, a control methodology of T/R modules output is proposed. Before the compensation is applied, 16 T/R modules integrated on the active SAR antenna show the amplitude in 28.2~29.0 dBm and the phase in $101.7^{\circ}{\sim}165.2^{\circ}$. After the compensation, the amplitude and phase are distributed in 27.4~28.0 dBm and $116.1^{\circ}{\sim}120.0^{\circ}$ respectively. The antenna beam patterns generated by the array theory with the distributions are compared, and the proposed method is verified as good to apply for the active SAR system.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.390-393
• /
• 2006

It is well known that synthetic aperture radar (SAR) provides information on ocean winds and surface waves. SAR data are of particularly high value in extreme weather conditions, as radar is able to penetrate the clouds providing information on different ocean surface processes. In this presentation some recent results on SAR observation of extreme wind and ocean wave conditions is summarised. Particular emphasize is put on the investigation of typhoons and extratropical cyclones in the North Pacific. The study is based on the use of ENVISAT ASAR wide swath images. Wide swath and scansar data are well suited for a detailed investigation of cyclones. Several examples like, e.g., typhoon Talim will be presented, demonstrating that these data provide valuable information on the two dimensional structure of the both the wind and the ocean wave field. Comparisons of the SAR observation with parametric and numerical model data will be discussed. Some limitations of standard imaging models like, e.g., CMOD5 for the use in extreme wind conditions are explained and modifications are proposed. Finally the study summarizes the capabilities of new high resolution TerraSAR-X mission to be launched in October 2006 with respect to the monitoring of extreme weather conditions. The mission will provide a spatialresolution up to 1m and has full polarimetric capabilities.

• Korean Journal of Remote Sensing
• /
• v.23 no.6
• /
• pp.501-506
• /
• 2007

Basic research is conducted to identify a target using corner reflectors which are commonly used in calibration of synthetic aperture radar (SAR) systems. At first, an omni-directional reflector is fabricated by combining four 15-cm rectangular trihedral corner reflectors. Then, its radar cross section (RCS) characteristics are measured at C-band (5.3 GHz) for vv-, hh-, hv-, and vh- polarizations at a range of horizontal angle, $-90^{\circ}{\le}{\phi}{\le}90^{\circ}$. The measured RCS angular variation of the omni-directional reflector is much smaller for vv-polarization than other polarizations, and the difference between the maximum and minimum RCSs for vv-polarization is about 8 dB. Peak RCS values are shown at $0^{\circ}$ (normal to plates) and $45^{\circ}$ (direction of bore sight). It is shown that the measurements agree quite well with numerical simulation and theoretical computation results.

• Current Industrial and Technological Trends in Aerospace
• /
• v.8 no.2
• /
• pp.98-104
• /
• 2010

The demand for Satellite Images is continuously increasing owing to the various applications of optical satellite images. However, the acquisition of optical images has a limitation due to problems of weather and day & night. because an optical satellite makes images with reflections of sunlight. Therefore, SAR Satellite, which uses electromagnetic waves to make an image, gives increased demand to various applications. It also makes increased interest. In this paper, a calibration and validation system, which is an essential element for high quality Radar images, is studied.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.28-28
• /
• 2022

본 연구는 용담댐유역을 포함한 금강 유역 상류 지역을 대상으로 Sentinel-1 SAR (Synthetic Aperture Radar) 위성영상을 기반으로 한 토양수분 산정을 목적으로 하였다. Sentinel-1 영상은 2019년에 대해 12일 간격으로 수집하였고, 영상의 전처리는 SNAP (SentiNel Application Platform)을 활용하여 기하 보정, 방사 보정 및 Speckle 보정을 수행하여 VH (Vertical transmit-Horizontal receive) 및 VV (Vertical transmit-Vertical receive) 편파 후방산란계수로 변환하였다. 토양수분 산정에는 Water Cloud Model (WCM)이 활용되었으며, 모형의 식생 서술자(Vegetation descriptor)는 RVI (Radar Vegetation Index)와 NDVI (Normalized Difference Vegetation Index)를 활용하였다. RVI는 Sentinel-1 영상의 VH 및 VV 편파자료를 이용해 산정하였으며, NDVI는 동기간에 대해 10일 간격으로 수집된 Sentinel-2 MSI (MultiSpectral Instrument) 위성영상을 활용하여 산정하였다. WCM의 검정 및 보정은 한국수자원공사에서 제공하는 10 cm 깊이의 TDR (Time Domain Reflectometry) 센서에서 실측된 6개 지점의 토양수분 자료를 수집하여 수행하였으며, 매개변수의 최적화는 비선형 최소제곱(Non-linear least square) 및 PSO (Particle Swarm Optimization) 알고리즘을 활용하였다. WCM을 통해 산정된 토양수분은 피어슨 상관계수(Pearson's correlation coefficient)와 평균제곱근오차(Root mean square error)를 활용하여 검증을 수행할 예정이다.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.24 no.1
• /
• pp.12-21
• /
• 2021

For successful automatic target recognition(ATR) with synthetic aperture radar(SAR) imagery, SAR target images of the database should have the identical or highly similar resolution with those collected from SAR sensors. However, it is time-consuming or infeasible to construct the multiple databases with different resolutions depending on the operating SAR system. In this paper, an approach for resolution conversion of SAR target images is proposed based on conditional generative adversarial network(cGAN). First, a number of pairs consisting of SAR target images with two different resolutions are obtained via SAR simulation and then used to train the cGAN model. Finally, the model generates the SAR target image whose resolution is converted from the original one. The similarity analysis is performed to validate reliability of the generated images. The cGAN model is further applied to measured MSTAR SAR target images in order to estimate its potential for real application.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.48 no.4
• /
• pp.285-293
• /
• 2020

In this paper, to improve Synthetic Aperture Radar (SAR) image quality, the effect of time synchronization error in the EGI/IMU (Embedded GPS/INS, Inertial Measurement Unit) integrated system is analyzed and state augmentation is applied to compensate it. EGI/IMU integrated system is widely used as a SAR motion measurement algorithm, which consists of EGI mounted to obtain the trajectory and IMU mounted on the SAR antenna. In an EGI/IMU integrated system, a time synchronization error occurs when the clocks of the sensors are not synchronized. Analysis of the effect of time synchronization error on navigation solutions and SAR images confirmed that the time synchronization error deteriorates SAR image quality. The state augmentation is applied to compensate for this and as a result, the SAR image quality does not decrease. In addition, by analyzing the performance and the observability of the time synchronization error according to the maneuver, it was confirmed that the time-variant maneuver such as rotational motion is necessary to estimate the time synchronization error adequately. In order to reduce the influence of the time synchronization error on the SAR image, the time synchronization error must be compensated by performing maneuver changing over time such as a rotation before SAR operation.

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

• Smart Structures and Systems
• /
• v.26 no.3
• /
• pp.277-290
• /
• 2020

Disasters, including earthquakes and landslides, have enormous economic and social losses besides their impact on environmental disruption. Iran, and particularly its Western part, is known as an earthquake susceptible area due to numerous strong ground motions. Studying ecological changes due to climate change can improve the public and expert sector's awareness and response to future disastrous events. Synthetic Aperture Radar (SAR) data and Interferometric Synthetic Aperture Radar (InSAR) technologies are appropriate tools for modeling and surface deformation modeling. This paper proposes an efficient approach to detect ground deformation changes using Sentinel-1A. The focal point of this research is to map the ground surface deformation modeling is presented using InSAR technology over Sarpol-e Zahab on 25^th November 2018 as a study case. For surface deformation modeling and detection of the ground movement due to earthquake SARPROZ in MATLAB programming language is used and discussed. Results show that there is a general ground movement due to the Sarpol-e Zahab earthquake between -7 millimeter to +18 millimeter in the study area. This research verified previous researches on the advanced image analysis techniques employed for mapping ground movement, where InSAR provides a reliable tool for assisting engineers and the decision-maker in choosing proper policies in a time of disasters. Based on the result, 574 out of 682 damaged buildings and infrastructures due to the 2017 Sarpol-e Zahab earthquake have moved from -2 to +17 mm due to the 2018 earthquake with a magnitude of 6.3 Richter. Results show that mountainous areas have suffered land subsidence, where urban areas had land uplift.