• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.2
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• pp.83-92
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• 2018

Using ground moving target indicators equipped with synthetic aperture radars for locating moving targets within a wide background clutter in a short time is an excellent method for monitoring traffic. Although the displaced phase center antenna (DPCA) technique and along track interferometry (ATI) are real time methods with low computational complexity, they are essential for reducing cases of false alarm that can result in poor performance. In this paper, we propose two detection methods using DPCA and ATI-the parallel fusion method and serial fusion method. Simulation results demonstrate that the proposed detection methods are characterized by low probability of false alarm along with good performance. In particular, the serial fusion method possesses high detection probability along with low probability of false alarm (1/5th of the false alarm probability of the DPCA technique).

• Journal of Navigation and Port Research
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• v.26 no.5
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• pp.543-548
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• 2002

It has been known that the DCMP(Directionally Constrained Minimization of Power) and the ZF(Zero Forcing) can improve the SINR performance of an array antenna system by using spatial signature of wireless channel. This paper analyzes the performance of DCMP and ZF in multiple scattering environments. To obtain the spatial signature of wireless channel. both DOA(Directional of Arrival) and AS(Angular spread) of the received signals were estimated by using ESPRIT. The performance of the DCMP and the ZF was analyzed theoretically. By computer simulation of SINR performance was evaluated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.54-55
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• 2009

The bandwidth of detecting radars used for military purpose is increasingly broadened, and recently, the frequency band of the detecting radars is expanding to millimeterwave bands c! the millimeterwave bands of 35 GHz and 94 GHz. Since, especially, it is essential and important to fabricate and develop EM wave absorber with the absorption ability more than 10 dB in 94 GHz band, the EM wave absorber was manufactured based on the design method by FDTD simulation As a result, the developed EM wave absorber with the composition ratio of Binder(CPE with additional materials) : Carbon = 70 : 30 wt.% has the thickness of 0.7 mm and the absorption ability more than 14 dB in the frequency range of 94 GHz.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.39-39
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• 2012

Data assimilation techniques have received growing attention due to their capability to improve prediction in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modelling software are based on a deterministic approach. In this study, we developed a hydrological modelling framework for sequential data assimilation, namely MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modelling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. In this software framework, sequential data assimilation based on the particle filters is available for any hydrologic models considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and radar rainfall estimates is assessed simultaneously in sequential data assimilation.

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.5
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• pp.27-35
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• 2019

Stealth technology is a technique to avoid detection from detectors such as radar and infrared seekers. In particular, detection by infrared signature is more threatening because infrared missiles detect heat from the aircraft itself. Therefore, infrared stealth technology is essential for ensuring the survival of aircraft and unmanned combat aerial vehicles (UCAV). In this study, we analyzed aerodynamic and infrared stealth performance in relation to UCAV nozzle design. Based on simulation results, a double serpentine nozzle was effective in reducing the infrared signature because it could shield high-temperature components in the engine. In addition, we observed that the infrared signature was reduced at the turning position of the duct located at the rear part of the double serpentine nozzle.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.61-68
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• 2018

This paper describes design of a 10.525 GHz self oscillating mixer semiconductor IC chip combining voltage controlled oscillator and frequency mixer using silicon CMOS technology for Doppler radar applications. The p-core type VCO included in the self oscillating mixer minimizes the noise contained in the transmitted signal. This noise minimization increases the sensing distance and acts in a direction favorable to the reaching distance and the sensitivity of the motion detection sensor. Simulation results for phase noise show that a VCO designed as a P-core has a noise characteristic of -106.008 dBc / Hz at 1 MHz offset and -140.735 dBc / Hz at 25 MHz offset compared to a VCO designed with N-core and NP-core showed excellent noise characteristics. If a self-oscillating mixer is implemented using a p-core designed VCO in this study, a motion sensor with excellent range and reach sensitivity will be produced.

• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.166-171
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• 2022

In this paper, we propose an algorithm to improve DoA(direction of arrival) estimation performance of the subspace-based method by generating high robustness correlation matrix of the signals incident on the uniformly linear array antenna. The existing subspace-based DoA estimation method estimates the DoA by obtaining a correlation matrix and dividing it into a signal subspace and a noise subspace. However, the component of the correlation matrix obtained from the low SNR and small number of snapshots inaccurately estimates the signal subspace due to the noise component of the antenna, thereby degrading the DoA estimation performance. Therefore a robust correlation matrix is generated by arranging virtual signal vectors obtained from the existing correlation matrix in a sliding manner. As a result of simulation using MUSIC and ESPRIT, which are representative subspace-based methods,, the computational complexity increased by less than 2.5% compared to the existing correlation matrix, but both MUSIC and ESPRIT based on RMSE 1° showed superior DoA estimation performance with an SNR of 3dB or more.

• Journal of Ocean Engineering and Technology
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• v.38 no.2
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• pp.64-73
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• 2024

Oil spills pose significant threats to marine ecosystems, human health, socioeconomic aspects, and coastal communities. Accurate real-time predictions of oil slick transport along coastlines are paramount for quick preparedness and response efforts. This study used an open-source OpenOil numerical model to simulate the fate and trajectories of oil slicks released during the 2007 Hebei Spirit accident along the Korean coasts. Six combinations of input parameters, derived from a five-day met-ocean dataset incorporating various hydrodynamic, meteorological, and wave models, were investigated to determine the input variables that lead to the most reasonable results. The predictive performance of each combination was evaluated quantitatively by comparing the dimensions and matching rates between the simulated and observed oil slicks extracted from synthetic aperture radar (SAR) data on the ocean surface. The results show that the combination incorporating the Hybrid Coordinate Ocean Model (HYCOM) for hydrodynamic parameters exhibited more substantial agreement with the observed spill areas than Copernicus Marine Environment Monitoring Service (CMEMS), yielding up to 88% and 53% similarity, respectively, during a more than four-day oil transportation near Taean coasts. This study underscores the importance of integrating high-resolution met-ocean models into oil spill modeling efforts to enhance the predictive accuracy regarding oil spill dynamics and weathering processes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.3
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• pp.385-396
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• 2024

To enhance the accuracy of sinkhole detection using GPR, this study derived a convolutional neural network that can optimally extract sinkhole characteristics from GPR B-scan grayscale images. The pre-trained convolutional neural network is evaluated to be more than twice as effective as the vanilla convolutional neural network. In pre-trained convolutional neural networks, fast feature extraction is found to cause less overfitting than feature extraction. It is analyzed that the top-1 verification accuracy and computation time are different depending on the type of architecture and simulation conditions. Among the pre-trained convolutional neural networks, InceptionV3 are evaluated as most robust for sinkhole detection in GPR B-scan grayscale images. When considering both top-1 verification accuracy and architecture efficiency index, VGG19 and VGG16 are analyzed to have high efficiency as the backbone for extracting sinkhole feature from GPR B-scan grayscale images. MobileNetV3-Large backbone is found to be suitable when mounted on GPR equipment to extract sinkhole feature in real time.