• Journal of the military operations research society of Korea
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• v.36 no.1
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• pp.15-27
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• 2010

Fire sequencing problem is to find a sequence of firing on the targets. The latest, because the korea artillery force is inferior in number as compared with north korea force. It is an important question to give a fatal damage to the enemy force by using prompt and accurate fire in order to overcome the lack of artillery force. Minimizing the fire finishing time will secure the adapt ability in tactical operation. In this paper, we developed a mathematical model to do allocation the fire on the targets to decrease to total fire operation time. In order to work out the fire sequencing problem, MIP is developed and the optimum solution is obtained by using ILOG OPL. If this analytical model is applied to the field artillery unit, it will improve the artillery fire force enhancement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.229-236
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• 2017

In general, an error budget of monopulse radar is proposed by manufacturer who assuming that all of external enviromental error resources such as multipath, glint, dynamic lag variation are removed. So until now, a measurement uncertainty of monopulse radar can be discussed including external enviromental error resources. In this paper, it is described that which kinds of error resource can effect on monopulse radar measurement uncertainty for different target property. To prove it experimentally, at first a simulation result is described assuming that all of external enviromental error resources are removed. It only includes receiver thermal noise. And then, monopulse radar measurement uncertainty estimation results tracking on calibration target which is fixed on specific position, calibration sphere which is moving slowly, weapon systems firing test which is moving fast are described quantitativly. All of these targets have different dynamic property.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.7
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• pp.737-747
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• 2013

A 3-D surveillance radar is a pulsed-doppler radar to provide various target information, such as range, doppler and angle by performing TWS. This paper introduces HW/SW architecture of radar signal processing board to process in real-time using high-speed multiple DSP(Digital Signal Processor) based on COTS. Moreover, we introduced a implemented algorithm consisted of clutter map creation/renewal, FIR(Finite Impulse Response) filter for rejection of zero velocity components, doppler filter, hybrid CFAR and finally presented computational burden of each algorithm by performing operational test using a beacon.

• Korean Journal of Optics and Photonics
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• v.19 no.4
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• pp.270-275
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• 2008

This paper addresses occluded object reconstruction and recognition with computational integral imaging (II). Integral imaging acquires and reconstructs target information in the three-dimensional (3D) space. The reconstruction is performed by averaging the intensities of the corresponding pixels. The distance to the object is estimated by minimizing the sum of the standard deviation of the pixels. We adopt principal component analysis (PCA) to classify occluded objects in the reconstruction space. The Euclidean distance is employed as a metric for decision making. Experimental and simulation results show that occluded targets are successfully classified by the proposed method.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.11-21
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• 2022

Two methods for analyzing interaction between shaped charge jets and targets are taken in AVEAM-MT (ADD Vulnerability and Effectiveness Assessment Model for Materiel Target), which is a model for vulnerability analysis of materiel targets and being developed by ADD. One is an empirical method improved from the Fireman-Pugh technique for rapid penetration calculation into target components. The other is ADD-TSC(ADD Tandem Shaped Charge), which is a physics-based model extended to be applicable for shaped charge jets from the Walker-Anderson penetration model for higher fidelity analysis. In this paper, the two methods are briefly described, and the empirical technique is compared to the physics-based model in the prediction of residual penetration capacity. The latter is also compared to experimental results found in literature in predicting penetration capacity. These comparisons show that both methods can be used for fast calculations or higher fidelity calculations in vulnerability analysis models like AVEAM-MT which is required to perform a considerable amount of iterative simulation for damage analysis.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.1
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• pp.12-21
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• 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 Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.219-230
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• 2022

In implementing a robust automatic target recognition(ATR) system with synthetic aperture radar(SAR) imagery, one of the most important issues is accurate classification of target variants, which are the same targets with different serial numbers, configurations and versions, etc. In this paper, a deep learning network with channel attention modules is proposed to cope with the recognition problem for target variants based on the previous research findings that the channel attention mechanism selectively emphasizes the useful features for target recognition. Different from other existing attention methods, this paper employs the channel attention modules without dimensionality reduction along the channel direction from which direct correspondence between feature map channels can be preserved and the features valuable for recognizing SAR target variants can be effectively derived. Experiments with the public benchmark dataset demonstrate that the proposed scheme is superior to the network with other existing channel attention modules.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2004.05a
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• pp.270-284
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• 2004

본 연구에서는 기업의 기술 사업화 타당성 평가 시, 기술성, 시장성 및 경제성 평가가 독립적으로 진행되는 것을 제고하고, 평가과정 중에서 자연스럽게 기술성과 사업성을 결합하여 인식할 수 있는 방법론적 틀을 제시하고자 하였다. 여기서는 크게 LSLP 개념을 도입한 기술기여율 분석과, 기술적 난이도 및 부가가치 창출율의 기하평균으로 구성된 기술의 제품기여도 분석으로 이를 파악하고자 하였으며, 이를 통해 도출된 결과들은 기술의 경제적 가치의 상대적 파악, 표적시장 및 기업의 기술 포트폴리오 구축에 활용되었다.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.2
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• pp.207-213
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• 2013

An infrared image synthetic method is proposed for infrared system simulation. The synthesis image uses a background IR image captured from real scene and a target IR modeling image. The radiances related with maximum and minimum temperatures of the background and target images are calculated from the Planck's blackbody equation. Based on them, the background and target images are compensated and synthesized. The proposed method is simulated and the IR target images are generated by RadThermIR software.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.5
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• pp.708-716
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• 2017

We deal with the target selection in seeker-detection image through network, using the detection information from aerial vehicle and the target information from surveillance and reconnaissance system. Especially, we constrain the sea battle environment, where it is difficult to perform scene-matching rather than land. In this paper, we suggest the target selection algorithm based on the confidence estimation with respect to distance and size. In detail, we propose the generation method of reference point for distance evaluation, and we investigate the effect of pixel margin and target course for size evaluation. Finally, the proposed algorithm is simulated and analyzed through several scenarios.