• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.283-298
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• 2022

As Synthetic Aperture Radar (SAR) image can be acquired regardless of the weather and day or night, it is highly recommended to be used for Automatic Target Recognition (ATR) in the fields of surveillance, reconnaissance, and national security. However, there are some limitations in terms of cost and operation to build various and vast amounts of target images for the SAR-ATR system. Recently, interest in the development of an ATR system based on simulated SAR images using a target model is increasing. Attributed Scattering Center (ASC) matching and template matching mainly used in SAR-ATR are applied to target classification. The method based on ASC matching was developed by World View Vector (WVV) feature reconstruction and Weighted Bipartite Graph Matching (WBGM). The template matching was carried out by calculating the correlation coefficient between two simulated images reconstructed with adjacent points to each other. For the performance analysis of the two proposed methods, the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset was used, which has been recently published by the U.S. Defense Advanced Research Projects Agency (DARPA). We conducted experiments under standard operating conditions, partial target occlusion, and random occlusion. The performance of the ASC matching is generally superior to that of the template matching. Under the standard operating condition, the average recognition rate of the ASC matching is 85.1%, and the rate of the template matching is 74.4%. Also, the ASC matching has less performance variation across 10 targets. The ASC matching performed about 10% higher than the template matching according to the amount of target partial occlusion, and even with 60% random occlusion, the recognition rate was 73.4%.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.9
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• pp.707-721
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• 2018

In this paper, a small synthetic aperture radar(SAR) system with 30 cm resolution is proposed, and a RAW data-based Doppler parameter estimation and motion compensation algorithm is described in detail. Acquisition of both PolSAR and InSAR data are enabled because there are two channels each in the transmitter and receiver modules. Automotive-based field work is performed to obtain PolSAR data, and signal processing results are ultimately obtained. A motion compensation algorithm is used to mitigate the residual phase error due to platform oscillation, and improved performance is obtained with the motion compensation algorithm using the automotive field test data.

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

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1415-1425
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• 2018

Kompsat-5 is the first Earth Observation Satellite which is equipped with an SAR in Korea. SAR images are generated by receiving signals reflected from an object by microwaves emitted from a SAR antenna. Because the wavelengths of microwaves are longer than the size of particles in the atmosphere, it can penetrate clouds and fog, and high-resolution images can be obtained without distinction between day and night. However, there is no color information in SAR images. To overcome these limitations of SAR images, colorization of SAR images using Cycle GAN, a deep learning model developed for domain translation, was conducted. Training of Cycle GAN is unstable due to the unsupervised learning based on unpaired dataset. Therefore, we proposed MS Cycle GAN applying multi-scale discriminator to solve the training instability of Cycle GAN and to improve the performance of colorization in this paper. To compare colorization performance of MS Cycle GAN and Cycle GAN, generated images by both models were compared qualitatively and quantitatively. Training Cycle GAN with multi-scale discriminator shows the losses of generators and discriminators are significantly reduced compared to the conventional Cycle GAN, and we identified that generated images by MS Cycle GAN are well-matched with the characteristics of regions such as leaves, rivers, and land.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.6
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• pp.503-512
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• 2018

SAR(Synthetic Aperture Radar) is a technology to acquire images by processing signals obtained from radar, and there is an increasing demand for utilization of high-resolution SAR images. In this paper, for high-speed processing of high-resolution SAR image data, a study for SAR image processing algorithms to achieve optimal performance in multi-core based computer architecture is performed. The performance deterioration due to a large amount of input/output data for high resolution images is reduced by maximizing the memory utilization, and the parallelization ratio of the code is increased by using dynamic scheduling and nested parallelism of OpenMP. As a result, not only the total computation time is reduced, but also the upper bound of parallel performance is increased and the actual parallel performance on a multi-core system with 10 cores is improved by more than 8 times. The result of this study is expected to be used effectively in the development of high-resolution SAR image processing software for multi-core systems with large memory.

• Journal of Satellite, Information and Communications
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• v.9 no.2
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• pp.74-79
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• 2014

Conventional ScanSAR mode has been adopted in Envisat or Radarsat and played an important role to acquire wide swath SAR images for environmental surveillance. However, it suffers from the undesirable scalloping effect caused by non-homogeneity of antenna pattern while the image resolution is sacrificed. In recent years, TOPS mode has been suggested and put into use to overcome the disadvantages of the conventional scanning mode. Although TOPS mode is able to produce wide-swath SAR image in a short time interval, it demands highly complicated system design knowledge. In this paper, we present the operation principle of TOPS mode and a full SAR simulation is performed to generate TOPS SAR raw data. Azimuth antenna pattern is modified during TOPS mode operation and it is shown that the undesired scalloping effect is suppressed in the generated SAR image.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.72-78
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• 2021

This paper proposes a wide-band dual-polarization stacked patch array antenna for satellite SAR system applications. The array antenna was designed for loss minimization and wide-band characteristics to enhance the performance of the SAR system and optimize it for active return loss in applications to active phased arrays. The fabricated array antenna showed a performance of 19.26%/19.79% fractional bandwidth within the -10 dB reference level of the active return loss and showed loss characteristics of 0.797 dB/0.799 dB averaged within the operational frequency for both H/V-polarization cases. The pattern performance was verified by comparing the measured patterns with the calculated patterns obtained by the array factor.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.206-214
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• 2022

The way to measure the extent of damage from floods and droughts is to identify changes in the extent of water systems. In order to effectively grasp this at a glance, satellite images are used. KOMPSAT-5 uses Synthetic Aperture Radar (SAR) to capture images regardless of weather conditions such as clouds and rain. In this paper, various deep learning models are applied to perform semantic segmentation of the water system in this SAR image and the performance is compared. The models used are U-net, V-Net, U2-Net, UNet 3+, PSPNet, Deeplab-V3, Deeplab-V3+ and PAN. In addition, performance comparison was performed when the data was augmented by applying elastic deformation to the existing SAR image dataset. As a result, without data augmentation, U-Net was the best with IoU of 97.25% and pixel accuracy of 98.53%. In case of data augmentation, Deeplab-V3 showed IoU of 95.15% and V-Net showed the best pixel accuracy of 96.86%.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.144-147
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• 2004

Two different sensors (here, KOMPSAT and RADARSAT) are considered for ship detection, and are used to delineate the detection performance for their data. The experiments are set for coastal regions of Mokpo Port and Ulsan Port and field experiments on board pilot boat are conducted to collect in situ ship validation information such as ship type and length. This paper introduce mainly the experiment result of ship detection by both RADARSAT SAR imagery and landbased RADAR data, operated by the local Authority of South Korea, so called vessel traffic system (VTS) radar. Fine imagery of Ulsan Port was acquired on June 19, 2004 and in-situ data such as wind speed and direction, taking pictures of ships and natural features were obtained aboard a pilot ship. North winds, with a maximum speed of 3.1 m/s were recorded. Ship's position, size and shape and natural features of breakwaters, oil pipeline and alongside ship were compared using SAR and VTS. It is shown that KOMPSAT/EOC has a good performance in the detection of a moving ship at a speed of 7 kts or more an hour that ship and its wake can be imaged. The detection capability of RADARSAT doesn't matter how fast ship is running and depends on a ship itself, e.g. its material, length and type. Our results indicate that SAR can be applicable to automated ship detection for a VTS and SAR combination service.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.11
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• pp.894-901
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• 2017

In the existence of motion, azimuth phase error due to accuracy limitation of GPS/IMU and system delay is unavoidable and it is essential to apply autofocus to estimate and compensate the azimuth phase error. In this paper, autofocus algorithm using MWLS(Modified WLS) is proposed. It shows the robust performance compared with original WLS using new target selection/sorting metric and iterative azimuth phase estimation technique. SAR raw data obtained in a captive flight test is used to validate the performance of the proposed algorithm.