• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.463-466
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• 2000

SAR imaging 시스템 전파환경에서 목표물의 정보를 성공적으로 추출해 내기 위해서는 반사된 신호를 수신할 때 Coherent detection이 필수적이다. 수신시 Incoherent detection은 복소 위상오차 형태로 나타나서 실제 목표물의 영상에 심각한 Degradation을 야기시켜 치명적인 결과를 초래하게된다. 본 논문에서는 하나의 목표물에서 수신되는 신호를 파동방정식으로부터 모델링하고 모델링된 신호의 각 주파수대의 조합에 의해 전체 수신신호로부터 위상오차의 기울기를 유도한다. 더욱더 정확한 위상오차를 추정하기 위해 추정된 위상오차로부터 수신신호에 포함된 오차를 제거하고, 오차가 제거된 신호의 대역폭을 추정한다. 추정된 대역폭에 맞도록 알고리즘에 재 적용시켜 교정되지 못한 오차를 추정해 나간다. 이때 반복적인 위상오차 제거기법을 적용하고 Iteration의 종료를 자동으로 결정하기 위해 지능형 대역폭 추정 기법을 제시한다. 컴퓨터의 모의 실험에서, 위상오차를 포함한 수신 신호로부터 알고리즘을 적용하여 오차를 제거하고,, Wavefront Reconstruction 기법에 적용시켜 알고리즘의 성능을 영상으로 확인한다.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1897-1902
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• 2005

The objective of this paper is to estimate the concentration distribution in flow field inside the pipeline based on electrical impedance tomography. Special emphasis is given to the development of dynamic imaging technique for two-phase field undergoing a rapid transient change. Nonlinearity-compensation extended Kalman filter is employed to cope with unexpected measurement uncertainty. The nonlinearity-compensation extended Kalman filter compensates for the influence of measurement uncertainty and solves the instability of extended Kalman filter. Extensive computer simulations are carried out to show that nonlinearity-compensation extended Kalman filter has enhanced estimation performance especially in the unexpected measurement environment.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.35-37
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• 2007

Super resolution using stochastic approach which based on the Bayesian approach is to easy modeling for a priori knowledge. Generally, the Bayesian estimation is used when the posterior probability density function of the original image can be established. In this paper, we introduced the improved MAP algorithm based on Bayesian which is stochastic approach in spatial domain. And we presented the observation model between the HR images and LR images applied with MAP reconstruction method which is one of the major in the SR grid construction. Its test results, which are operation speed, chip size and output high resolution image Quality. are significantly improved.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.379-380
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• 2007

In this paper, we propose the fast hi-linear interpolation method for SR reconstruction. This method reconstructs the HR image rapidity by considering motion vector information for each LR input image. And its calculation used normalized deviation of image data. As using the motion vector information which is obtained at registration error checking process, this proposed can be achieved the fast and simple SR reconstructed image.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.12
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• pp.561-566
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• 2005

This paper introduces a compression technique for power qualify disturbance signal via discrete wavelet transform(DWT). The proposed approach is based on a previous estimation of the stationary component of power quality disturbance signal, so that it could be subtracted from the original signal in order to reduce a dynamic range of signal and generate transient events signal, which is subsequently applied to the compression technique. The compression techniques is performed through the difference signal decomposition, thresholding of wavelet coefficients, and signal reconstruction. It presents the relation between compression efficiency and threshold. It shouts that the wavelet transform leads to a power quality data compression approach with high compression efficiency, small compression error and good de-nosing effect.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1153-1164
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• 2024

In recent years, unmanned ground vehicles (UGVs) have been used to search for lost or stolen radioactive sources to avoid radiation exposure for operators. To achieve autonomous localization of radioactive sources, the UGVs must have the ability to automatically determine the next radiation measurement location instead of following a predefined path. Also, the radiation field of radioactive sources has to be reconstructed or inverted utilizing discrete measurements to obtain the radiation intensity distribution in the area of interest. In this study, we propose an effective source localization framework and method, in which UGVs are able to autonomously explore in the radiation area to determine the location of radioactive sources through an iterative process: path planning, radiation field reconstruction and estimation of source location. In the search process, the next radiation measurement point of the UGVs is fully predicted by the design path planning algorithm. After obtaining the measurement points and their radiation measurements, the radiation field of radioactive sources is reconstructed by the Gaussian process regression (GPR) model based on machine learning method. Based on the reconstructed radiation field, the locations of radioactive sources can be determined by the peak analysis method. The proposed method is verified through extensive simulation experiments, and the real source localization experiment on a Cs-137 point source shows that the proposed method can accurately locate the radioactive source with an error of approximately 0.30 m. The experimental results reveal the important practicality of our proposed method for source autonomous localization tasks.

• Korean Journal of Applied Biomechanics
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• v.15 no.2
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• pp.83-92
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• 2005

Computer-assisted motional analysis is a popular method in biomechanical studies. Validation of the specific system and its measurement are fundamental to its application in the areas. Because the accuracy and consistency of a particular system provide the researchers with critical information to assist in making judgements regarding the degree to which inferences can be drawn from measurement data. The purpose of this study was to assess the accuracy and consistency of the Kwon3D motion analysis system. Validation parameters were five lengths from eight landmarkers in combination with the DLT reconstruction error values, digitizing monitor resolutions, and numbers of control points. With the best setting, Kwon3D's estimations of 260cm, 200cm, 140cm, 100cm, and 20cm were $260.33{\pm}.688cm$, $199.98{\pm}.625cm$, $139.89{\pm}.537cm$, $99.75{\pm}.466cm$, $20.08{\pm}.114$, respectively. There was no significant DLT error value difference between two monitor resolutions, but 0.27cm significant difference in 260cm estimation. There were significant differences in 260cm and 200cm estimations between with 33-control-point DLT error and with 17-control-point DLT error, but no in 140cm, 100cm, and 20cm estimations. Test-retest results showed that Kwon3D measurements were highly consistent with reliability coefficients alpha of .9263 and above.

• Korea Real Estate Review
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• v.24 no.1
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• pp.7-14
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• 2014

This study, as the temporal and spatial data for the real price apartment in Seoul from January 2006 to June 2013, empirically compared and analyzed the estimation result of apartment price using OLS by hedonic price model for the problem of space-time correlation, temporal autoregressive model (TAR) considering temporal effect, spatial autoregressive model (SAR) spatial effect and spatiotemporal autoregressive model (STAR) spatiotemporal effect. As a result, the adjusted R-square of STAR model was increased by 10% compared that of OLS model while the root mean squares error (RMSE) was decreased by 18%. Considering temporal and spatial effect, it is observed that the estimation of apartment price is more correct than the existing model. As the result of analyzing STAR model, the apartment price is affected as follows; area for apartment(-), years of apartment(-), dummy of low-rise(-), individual heating (-), city gas(-), dummy of reconstruction(+), stairs(+), size of complex(+). The results of other analysis method were the same. When estimating the price of real estate using STAR model, the government officials can improve policy efficiency and make reasonable investment based on the objective information by grasping trend of real estate market accurately.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.3
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• pp.331-337
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• 2016

In this paper, we analyze performances of in-band full-duplex communication system and self-interference (SI) suppression methods in environment where there exists the SI signal. The SI has to be removed to achieve required error rate performance of the system in order - propagation domain, analog domain and digital domain. In propagation domain, the SI signal is attenuated by separating transmitted and received beams physically. In analog and digital domain, after reconstruction of the SI signal using channel estimates and transmit signal, the SI signal can be cancelled from the desired signal. In this paper, assuming that the SI signal can be sufficiently reduced in propagation domain, we demonstrate that the in-band full-duplex communication system can achieve the target error rate by suppressing the SI signal in order - analog and digital domain, based on channel estimates that can be obtained by the method of Least squares.

• Journal of Broadcast Engineering
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• v.1 no.2
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• pp.176-187
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• 1996

This paper deals with the accurate estimation of 3- D pose (position and orientation) of a moving object with reference to the world frame (or robot base frame), based on a sequence of stereo images taken by cameras mounted on the end - effector of a robot manipulator. This work is an extension of the previous work[1]. Emphasis is given to the 3-D pose estimation relative to the world (or robot base) frame under the presence of not only the measurement noise in 2 - D images[ 1] but also the camera position errors due to the random noise involved in joint angles of a robot manipulator. To this end, a new set of discrete linear Kalman filter equations is derived, based on the following: 1) the orientation error of the object frame due to measurement noise in 2 - D images is modeled with reference to the camera frame by analyzing the noise propagation through 3- D reconstruction; 2) an extended Jacobian matrix is formulated by combining the result of 1) and the orientation error of the end-effector frame due to joint angle errors through robot differential kinematics; and 3) the rotational motion of an object, which is nonlinear in nature, is linearized based on quaternions. Motion parameters are computed from the estimated quaternions based on the iterated least-squares method. Simulation results show the significant reduction of estimation errors and also demonstrate an accurate convergence of the actual motion parameters to the true values.