• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.2
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• pp.183-194
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• 2011

Synthetic aperture radar (SAR) is widely used because of high resolution imaging capability in all weather and day/night condition. In this paper development of Spotlight SAR simulator is proposed for image quality analysis. Proposed SAR simulator is based on the SAR system design parameters so that SAR image performance can be expected which is essential throughout the full system development procedure from the initial concept design stage to the final in-flight calibration and validation stage. The raw data of ideal point target is first generated by taking account of the flight and imaging geometry and the various SAR system design parameters, and the Spotlight image formation algorithm is implemented in order to obtain the point target response. Finally the image quality of the generated raw data is analyzed in terms of spatial resolution, peak to sidelobe ratio and integrated sidelobe ratio.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.144-150
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• 2022

The on-board processor of satellite synthetic aperture radar(SAR) generates transmission signal by digital signal processing, converts it into an analog signal. At this time, the transmission signal generated from the baseband requires the frequency modulation to convert it to the high-frequency band in order to improve the stability. General frequency modulation method using local oscillator(LO) causes IQ imbalance due to phase error/magnitude error and these error reduce performance of SAR. To generate transmission signal without phase/magnitude error, this paper suggests design method of the frequency modulation method using digital to analog converter(DAC) at on-board SAR. For design, this paper analyzes the characteristic of DAC mode and uses pre-compensation filter. To analyze the proposed method performance, performance index are compared with IQ imbalance signals. This method is suitable for on-board SAR using fast sampling DAC and has the advantage of being able to solve IQ imbalances.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.141-150
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• 2024

Ground subsidence in urban areas is mainly caused by anthropogenic factors such as excessive groundwater extraction and underground infrastructure development in the subsurface composed of soft materials. Global Navigation Satellite System data with high temporal resolution have been widely used to measure surface displacements accurately. However, these point-based terrestrial measurements with the low spatial resolution are somewhat limited in observing two-dimensional continuous surface displacements over large areas. The synthetic aperture radar interferometry (InSAR) technique can construct relatively high spatial resolution surface displacement information with accuracy ranging from millimeters to centimeters. Although constellation operations of SAR satellites have improved the revisit cycle, the temporal resolution of space-based observations is still low compared to in-situ observations. In this study, we evaluate the extraction of a time-series of surface displacement in Incheon Metropolitan City, South Korea, using the small baseline subset technique implemented using the commercial software, Gamma. For this purpose, 24 COSMO-SkyMed X-band SAR observations were collected from July 12, 2011, to August 27, 2012. The time-series surface displacement results were improved by reducing random phase noise, correcting residual phase due to satellite orbit errors, and mitigating nonlinear atmospheric phase artifacts. The perpendicular baseline of the collected COSMO-SkyMed SAR images was set to approximately 2-300 m. The surface displacement related to the ground subsidence was detected approximately 1 cm annually around a few Incheon Subway Line 2 route stations. The sufficient coherence indicates that the satellite orbit has been precisely managed for the interferometric processing.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.392-400
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• 2021

Unlike optical equipment, SAR(Synthetic Aperture Radar) has the advantage of obtaining images in all weather, and object detection in SAR images is an important issue. Generally, deep learning-based object detection was mainly performed in real-valued network using only amplitude of SAR image. Since the SAR image is complex data consist of amplitude and phase data, a complex-valued network is required. In this paper, a complex-valued ResNet network is proposed. SAR image object detection was performed by combining the ROI transformer detector specialized for aerial image detection and the proposed complex-valued ResNet. It was confirmed that higher accuracy was obtained in complex-valued network than in existing real-valued network.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.8
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• pp.599-607
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• 2018

This paper presents a ground-to-air bistatic radar system and its implementation algorithm, which resembles an SAR(synthetic aperture radar) reconstruction algorithm. Via cooperative working between a standoff transmitting radar and an array of ground based receiving radars, it detects and images moving targets under clutter in the air. In the proposed system, the whole receiving antenna aperture is synthesized by physical ground based radars, and thus, unlike conventional SAR, it does not require long illumination time of the target area. The reconstruction algorithm uses planewave approximation based polar format processing, which alleviates the requirement of positioning the receiving radars, which can cause grating lobes if not chosen properly. We derive a reconstruction algorithm including clutter suppression and discuss implementation issues, such as the resolution of a reconstructed image and the method of compensation for the irregularity of the receiving radars' positions. A simulation that validates the proposed algorithm is also shown.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.6
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• pp.663-668
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• 2008

Recently, World Radio Conference(WRC)-2007 approved the ultrawide bandwidth of 500 MHz for the use of spaceborne synthetic aperture radar in X-band for the EESS(Earth Exploration Satellite Service) in order to improve the SAR imaging resolution. It is concerned about the interference impact from the spaceborne SAR that may cause to most of ground radars due to the extended ultra wideband. In this paper, in order to predict the interference impact of the ground-based radar from the spaceborne radar, radar interference model is presented using radar characteristic parameters by taking into account the operating environments of the spaceborne and ground based radar in the time, space, and spectrum domains. Using the spaceborne SAR model of TerraSAR-X and ground radar model of meteorological radar recommended by ITU-R, the interference impact was assessed through the computer simulation to see the possible interference impact of the ground based radar operating in the Korean peninsula.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.3
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• pp.186-194
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• 2017

In this paper, we analyze the main performance of satellite's Synthetic Aperture Radar system for high resolution and wide swath. We have used the radiation pattern of reflector antenna with array feed and comparison between the conventional ScanSAR mode and SweepSAR mode has been carried out. The SweepSAR mode is a high-resolution wide-swath mode that transmits beams over a wide range and receives echo signals through sequential beamforming based on SCORE(SCan On REceive). In this paper, we analyzed the operating principle and characteristics of satellite's SweepSAR mode and simulate system performances. In addition, in order to increase the utilization of image, performances analysis for multiple frequency bands(C-band, X-band) has been considered.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1401-1411
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• 2023

In the face of escalating utilization of the marine spatial domain, conflicts have emerged among stakeholders, necessitating effective management strategies beyond conventional government permits and regulations. Particularly within the domain of aquaculture, operational oversight relies on a localized licensing system, posing challenges in accurately assessing the prevailing circumstances. This research employs synthetic aperture radar (SAR) imagery as a tool to monitor coastal aquaculture fish farms, aimed at enhancing insights into management protocols. Leveraging Sentinel-1A imagery and time series SAR data integration, a superimposition technique is utilized, facilitating noise reduction while retaining crucial information regarding smaller-scale facilities, such as fish farms. Through analysis of VH polarization data, a detection overall accuracy of approximately 88% for coastal fish farms was achieved. The findings of this study offer potential applications in the continuous monitoring of aquaculture farms in correspondence with seasonal variations in aquaculture yields, thereby proposing frameworks for the establishment of effective management cycles for marine space utilization.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.167-177
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• 2024

With advancements in satellite technology, interest in target detection and identification is increasing quantitatively and qualitatively. Synthetic Aperture Radar(SAR) images, which can be acquired regardless of weather conditions, have been applied to various areas combined with machine learning based detection algorithms. However, conventional studies primarily focused on the detection of stationary targets. In this study, we proposed a method to identify moving targets using an algorithm that integrates sub-aperture SAR images and cosine similarity calculations. Utilizing a transformer-based deep learning target detection model, we extracted the bounding box of each target, designated the area as a region of interest (ROI), estimated the similarity between sub-aperture SAR images, and determined movement based on a predefined similarity threshold. Through the proposed algorithm, the quantitative evaluation of target identification capability enhanced its accuracy compared to when training with the targets with two different classes. It signified the effectiveness of our approach in maintaining accuracy while reliably discerning whether a target is in motion.

• Spatial Information Research
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• v.22 no.1
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• pp.27-33
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• 2014

Considering the wide coverage, the transparency from climate condition, Interferometric Synthetic Aperture Radar (InSAR) possesses a great potential for the landcover classification as shown in many precedent researches. In addition to the merits of InSAR products for the landcover classification, the time series analysis of InSAR pairs can provide a highly reliable basis to interpret landcover. We applied such idea with the test site in Mountain Baekdu located on the border between North Korea and China. Since it is recently noted as the potential volcanic activation site, the landcover especially the vegetation distribution information is highly essential to validate the reliability of Differential Interferometric Synthetic Aperture Radar (DInSAR) over Mt. Baekdu. The algorithms combining the auxiliary information from Moderate Resolution Imaging Spectroradiometer (MODIS) to analyze the phase coherence and backscatter coefficient of Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) was established. The results using InSAR signatures from two polarization modes of ALOS PALSAR showed high reliability for mining landcover and spatial distribution.