• Current Industrial and Technological Trends in Aerospace
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• v.7 no.1
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• pp.113-118
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• 2009

In this paper, we described the model of noise, target for tracking radar and range tracking, angle tracking, and Doppler frequency tracking for target acquisition and tracking. Target signal as well as the noise signal is modeled as random process varying with elapsed time. This paper addresses three areas of radar target tracking: range tracking, angle tracking, and Doppler frequency tracking. In general, range tracking is prerequisite to and inherent in both angle and Doppler frequency tracking systems. First, we introduced the several range tracking and described techniques for achieving range tracking. Second, we described the radar angle tracking techniques including conical scan, sequential lobing, and monopulse. Finally, we presented concepts and techniques for Doppler frequency tracking for several radar types.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.441-445
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• 2011

본 논문에서는 적외선 스테레오 카메라를 이용하여 고속으로 날아가는 표적의 좌표들을 측정하고 회귀분석을 통한 오차특성을 이용하여 추정하는 시스템을 제안한다. 표적과 배경의 온도차이로 표적 영역을 검출하고 적외선 스테레오 카메라 정합과 카메라 파라미터를 이용하여 표적의 좌표를 추정한다. 본 논문에서 제안하는 적외선 스테레오 카메라 시스템을 검증하기 위해 3차원 궤적(x,y,z) 측정기로 표적의 속도와 거리를 측정하여 표적 궤도를 예측하고, 여러 차례 실험한 비디오 데이터로부터 스테레오 정합을 이용하여 z, x축의 거리(좌표)들을 구하고 회귀 분석(regression analysis)을 사용하여 최소 자승법(Least squares method)으로 표적의 궤적들을 비교하였다. 적외선 스테레오 정합 시스템에 오차특성을 적용하여 표적의 좌표를 보정할 수 있었다. 향후 다양한 표적들의 오차를 모델화하여 고속표적들의 좌표 측정을 향상 시킬 수 있을 것으로 기대된다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.34-42
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• 1999

Multi-target tracking system is defined as tracking several targets simultaneously. Kalman filter is widely used for target tracking problems. Kalman filter is known to be extremely useful as an optimal estimator but has a shortcoming of computational complexity. So a simplified estimator model which had less computational burden is proposed for a real-time implementation of multi-target tracking systems. In this paper, Kalman filter is applied to implement a real-time tracking system with a simplified target model. The proposed Kalman filter model is simpler compared with those of conventional ones, greatly reducing computation time, yet keeping the tracking abilities of the optimal Kalman filter. Through both simulations and experiments with real environments, it is demonstrated that the proposed simplified model works good in real situation with multiple to be tracked.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.29-34
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• 1997

The prediction of detection range of a passive sonar system is essential to estimate the performance and to optimize the operation of a developed sonar system. In this paper, a model for the prediction of detection range in a range-dependent ocean environment based on the sonar equation is developed and tested. The prediction model calculates the transmission loss using PE propagation model, signal excess, and the detection probability at each target depth and range. The detection probability is integrated to give the estimated detection range. In order to validate the developed model, two cases are considered. One is the case when target depth is known. The other is the case when the target depth is unknown. The computational results agree well with the previously published results for the range-independent environment. Also,the developed model is applied to the range-dependent ocean environment where the warm eddy exists. The computational results are shown and discussed. The developed model can be used to find the optimal frequency of detection, as well as the optimal search depth for the given range-dependent ocean environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4A
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• pp.316-323
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• 2002

In this paper, we propose a counter-countermeasure (CCM) in a crossed array tracker for efficient target tracking under countermeasures (CM) operated by a target. The proposed CCM adepts two detection bands and uses the signal distribution characteristics to discriminate between the target and the CMs. To avoid wrong detection of a target position due to missing signal pulses, it predicts current target position based on previous target position. To evaluate the performance of the proposed CCM in a crossed array tracker, we perform numerical simulations for target signal extraction and target tracking under various conditions. The simulation results show that the proposed CCM removes the CM effect well and tracks the target efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1826-1834
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• 2021

In this paper, we check the possibility of continuous tracking when photographing unknown space objects in a short period of time in an optical observation system on the ground. Simulated observation data were generated for target limited to low-orbit areas. The performance index of the prediction error was set in consideration of the property of targets. Kalman Filter was applied to predict the next location of the target. A constant velocity/acceleration dynamic model was applied to the two axes of the azimuth/elevation of the unknown space object respectively. As a result of performing the Monte Carlo simulation, the maximum error ratio of the maximum nonlinear section was less than 2%, which could be determined to ensure continuous tracking. The CA model had little change in the prediction error value for each case, making it more suitable for tracking unknown space objects. This analysis could provide a foundation for determining the orbit of unknown space objects using optical observation.

• Clinical and Experimental Pediatrics
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• v.49 no.5
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• pp.552-557
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• 2006

Purpose : The recent results observed in precocious puberty and the hope that interrupting puberty might increase adult height have led to an attempt to use GnRH agonist(GnRHa) in children with premature puberty and a poor growth prognosis. We aimed to analyze the growth promoting effect of GnRHa in girls with early puberty and low predicted adult height(PAH). Methods : Thirty six girls were recruited. They were grouped according to the GnRHa treatment period(group 1>6 mo, n=18; group 2<6 mo, n=18). The following variables were analyzed before and after GnRHa treatment : chronological age(CA), bone age(BA), ${\Delta}age$(CA-BA), height, target height (TH), PAH, serum IGF-1, IGFBP-3. Results : Duration of the GnRHa treatment was $0.89{\pm}0.81yr$($1.37{\pm}0.92yr$ in group 1, and $0.41{\pm}0.08yr$ in group 2). Before treatment, none of the variables were different between the two groups. There were no differences in the following variables the between two groups at the end of treatment : CA, BA, ${\Delta}age$, PAH, serum IGF-1, IGFBP-3. But, growth velocity(GV) and PAH increment during treatment were significantly reduced in group 1. Compared with initial PAH, PAH at the end of treatment was significantly increased($3.7{\pm}3.2cm$). The last serum levels of IGF-1 and IGFBP-3 were lower than those before treatment. Conclusion : Even though last PAH didn't approach TH, short term GnRHa administration in early puberty with low predicted PAH was somewhat effective. But, GnRHa administration suppressed the growth hormone-IGF-1 axis. Therefore, it is recommended that growth hormone(GH) should be used in combination with GnRHa.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.11-18
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• 2021

This paper shows the applicability of deep learning algorithm in predicting target position and getting correction value of impact point in order to improve the accuracy of naval gun firing. Predicting target position, the proposed model using LSTM model and RN structure is expected to be more accurate than existing method using kalman filter. Getting correction value of impact point, the another proposed model suggests a reinforcement model that manages factors which is related in ballistic calculation as data set, and learns using the data set. The model is expected to reduce error of naval gun firing. Combining two models, a ballistic calculation model for improving accuracy of naval gun firing based on deep learning algorithm was designed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.3
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• pp.299-309
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• 2013

A comprehensive SAR(Synthetic Aperture Radar) simulation is considered to be a complicated task since a full knowledge of the signal propagation characteristics, antenna pattern, system internal errors and interference noises should be taken into account. In high resolution target application modes, the time varying nature of target RCS(Radar Cross Section) strongly affects the generated SAR images. In this paper, in-depth SAR simulations are performed and analyzed incorporating the STK tools and MATLAB software. STK provides realistic orbit parameters while its radar module helps to extract accurate radiometric parameters of ground targets. SAR raw data corresponding to a given target is generated and processed using MATLAB simulator. The performance is measured by PSLR(Peak Sidelobe Ratio) and ISLR(Integrated Sidelobe Ratio) for a point target, which can be used as reference parameters for accurate radiometric calibration. Finally, high resolution target simulations are performed by adopting time varying target RCS characteristics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.8-16
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• 2010

This paper presents a new small target detection method using the cross product of the temporal pixels based on the temporal profile in infrared (IR) image sequences. The temporal characteristics of small targets and the various backgrounds are different. A new algorithm classifies target pixels and the background pixels through the hypothesis testing using the cross product of pixels on the temporal profile and predicts the temporal backgrounds based on the results. The small targets are detected by subtracting the predicted temporal background profile from the original temporal profile. For the performance comparison between the proposed algorithm and the conventional algorithms, the receiver operating characteristics (ROC) curves is computed in experiment. Experimental results show that the proposed algorithm has better discrimination and a lower false alarm rate than the conventional methods.