• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.4
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• pp.308-315
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• 2018

In this paper, we present the basic design results for high-resolution radar development at S-band frequency that can precisely measure the miss distance between two targets. The basic system requirement is proposed for the design of a 3.5 GHz linear frequency-modulated (LFM) radar with maximum detection distance and distance resolution of 2 km and 1 m, respectively, and the specifications of each module are determined using the radar equation. Our calculations revealed a signal-to-noise ratio ${\geq}30dB$ with a bandwidth of 150 MHz, transmission power of 43 dBm for the power amplifier, gain of 26 dBi for the antenna, noise figure of 8 dB, and radar cross-section of $1m^2$ at a target distance of 2 km from the radar. Based on the calculation results and the theory and method of LFM radar design, the hardware was designed using software defined radar technology. The results of the subsequent field test are presented that prove that the designed radar system satisfies the requirements.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5103-5115
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• 2015

In radar imaging, a target is usually consisted of a few strong scatterers which are sparsely distributed. In this paper, an improved sparse signal recovery algorithm based on smoothed l₀ (SL0) norm method is proposed to achieve high resolution ISAR imaging with limited pulse numbers. Firstly, one new smoothed function is proposed to approximate the l₀ norm to measure the sparsity. Then a single loop step is used instead of two loop layers in SL0 method which increases the searching density of variable parameter to ensure the recovery accuracy without increasing computation amount, the cost function is undated in every loop for the next loop until the termination is satisfied. Finally, the new set of solution is projected into the feasible set. Simulation results show that the proposed algorithm is superior to the several popular methods both in terms of the reconstruction performance and computation time. Real data ISAR imaging obtained by the proposed algorithm is competitive to several other methods.

• Journal of Korea Multimedia Society
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• v.18 no.7
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• pp.793-805
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• 2015

Nowadays the amount of data obtained from advanced weather radars is growing to provide higher spatio-temporal resolution. Accordingly radar data compression is important to use limited network bandwidth and storage effectively. In this paper, we proposed a hierarchical compression method for weather radar data having high spatio-temporal resolution. The method is applied to radar reflectivity and evaluated in aspects of accuracy of quantitative rainfall intensity. The technique provides three compression levels from only 1 compressed stream for three radar user groups-signal processor, quality controller, weather analyst. Experimental results show that the method has maximum 13% and minimum 33% of compression rates, and outperforms 25% higher than general compression technique such as gzip.

• Journal of electromagnetic engineering and science
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• v.15 no.1
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• pp.37-43
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• 2015

We implemented a real-time radar system for an unmanned ground vehicle designed to run on unpaved or bumpy roads. The system must be able to detect slow targets in a cluttered environment and cover wide angular sections with high resolution at the same time. The system consists of array antennas, preprocessors for digital beam forming, and digital signal processors for the detection process which uses sawtooth waveforms and high-resolution estimation, and is called forward/backward spatial smoothing beamspace multiple signal classification (FBSS BS-MUSIC). We show that the sawtooth waveforms enhance the angular estimation capability of FBSS BS-MUSIC in addition to their well-known advantages of removing the ambiguity of targets and detecting slow targets with improved velocity resolution.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.3
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• pp.294-303
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• 2008

ISAR(Inverse Synthetic Aperture Radar) images represent the 2-D(two-dimensional) spatial distribution of RCS (Radar Cross Section) of an object, and they can be applied to the problem of target identification. A traditional approach to ISAR imaging is to use a 2-D IFFT(Inverse Fast Fourier Transform). However, the 2-D IFFT results in low resolution ISAR images especially when the measured frequency bandwidth and angular region are limited. In order to improve the resolution capability of the Fourier transform, various high-resolution spectral estimation approaches have been applied to obtain ISAR images, such as AR(Auto Regressive), MUSIC(Multiple Signal Classification) or Modified MUSIC algorithms. In this study, these high-resolution spectral estimators as well as 2-D IFFT approach are combined with a recently developed ISAR image classification algorithm, and their performances are carefully analyzed and compared in the framework of radar target recognition.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.3
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• pp.44-51
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• 2001

In general, the realization of spaceborne system is constrained by its space environment. In this paper, we suggest chirp stitching technique which generates and processes wideband radar signal with minimum hardware, design and implement transmit/receive equipments and operating programs to satisfy the requirement of this spaceborne high resolution SAR(Synthetic Aperture Radar). We apply the top down design approach to this system, and divide hardware into equipment, module and circuit levels, and software into SR(Software Requirement), AD(Architecture Design), DD(Detailed Design) and coding levels, and then extract each requirement to satisfy the wideband requirement of this spaceborne high resolution SAR. We, at first, test the hardware functions, confirm the wideband handling capability of this system with 85MHz wideband signals generated from two 42.5MHz narrow band signals, and show that this system can be used in spaceborne high resolution SARs.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.166-166
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• 2020

Recently, As the frequency of localized heavy rains increases, the use of high-resolution radar data is increasing. The produced radar rainfall has still gaps of spatial and temporal compared to gauge observation rainfall, and in many studies, various statistical techniques are performed for correct rainfall. In this study, the precipitation correction of the S-band Dual Polarization radar in use in the flood forecast was performed using the ConvAE algorithm, one of the Convolutional Neural Network. The ConvAE model was trained based on radar data sets having a 10-min temporal resolution: radar rainfall data, gauge rainfall data for 790minutes(July 2017 in Cheongju flood event). As a result of the validation of corrected radar rainfall were reduced gaps compared to gauge rainfall and the spatial correction was also performed. Therefore, it is judged that the corrected radar rainfall using ConvAE will increase the reliability of the gridded rainfall data used in various physically-based distributed hydrodynamic models.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.2
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• pp.128-137
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• 2018

In this paper, we propose a novel class separability measure for radar signals. To reduce the sensitivity of the relative aspect angle between a target and radar, to evaluate the discriminatory power of radar signals, the proposed method first calculates the correlation coefficients between two radar cross sections (RCSs) or linearly shifts one-dimensional (1D) radar signals (i.e., high-resolution range profiles (HRRPs)), or rotates two 2D radar signals (i.e., inverse synthetic aperture radar (ISAR) images). Then, it uses the maximum correlation coefficient when two radar signals are best aligned. Next, the proposed method obtains new correlation-based discriminant matrices (CDM) using maximum correlation coefficients. Finally, the cumulative distribution function (CDF) in the CDM and the value corresponding to the specific probability in the CDF are obtained, and this value represents the discriminatory power of the radar signal. Experimental results show that the proposed method can accurately measure the target separability.

• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.131-141
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• 2014

Synthetic Aperture Radar (SAR) is a powerful and well established microwave remote sensing technique which enables high resolution measurements of the Earth surface independent of weather conditions and sunlight illumination. In this study, this paper first summarizes the basic SAR theory and the history of the SAR satellites. The second part of this paper gives an overview of new technologies for future SAR systems. New innovative concepts and technologies for SAR satellites will be digital beamforming, High Resolution Wide Swath (HRWS), Waveform Encoding, Terrain Observation by Progressive Scan (TOPS), and so on. These technologies will play an important role for future spaceborne SAR satellites.