• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.546-555
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• 2009

There is increasingly interested in the measurement of antenna's characteristics for one's manufacture according to one's various application. Due to this, the antenna measurement system need be made with more and more great precision. On measuring of the antenna's characteristic, the conventional system handled by human generates the error due to controlling the position of the system by user. Therefore there need be introduced the automatic measurement system of antenna's characteristic. In this paper, we propose antenna extraction algorithm for the Antenna automatic measurement system of antenna's characteristic. The proposed algorithm gets the antenna image from antenna measurement system, extracts an antenna object from the image, and extracts the parameters for antenna's slant and antenna's location. The extracted parameters is used to correct location and distortions of the antenna and automatic measurement. The proposed algorithm is applied to the patch antenna. The results show that antenna's object is efficiently extracted and the angle for correcting the error is calculated well.

• Journal of Navigation and Port Research
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• v.38 no.2
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• pp.121-126
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• 2014

This paper suggests a new algorithm to provide low-cost GPS modules with DGPS service, which corrects the error vector in the already-calculated position by projecting range corrections to position domain using the observation matrix calculated from the satellite elevation and azimuth angle in the NMEA GPGSV data. The algorithm reduced the horizontal and vertical RMS error of U-blox LEA-5H module from 1.8m/5.8m to 1.0m/1.4m during the daytime. The algorithm has advantage in improving the performance of low-cost module to that of DGPS receiver by a software update without any correction in hardware, therefore it is expected to contribute to the vitalization of the future high-precision position service infrastructure by reducing the costumer cost and vender risk.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.382-385
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• 2007

Constantly enhancing positioning accuracy by the Global Positioning System (GPS) technique is of great importance, but challenging, especially after the GPS positioning technique has been improved considerably during the past two decades. The associated main error sources have been reduced substantially, if not eliminated. Troposhpeic influence with its highly temporal and spatial variability appears to be one of the major error sources. It is hence an increased interest among GPS researchers to reduce the tropospheric influence or delay. Two techniques have been commonly implemented to correct the tropospheric impact. The first technique, known as parameter estimation, characterizes the path delay with empirical models and the parameters of interest are determined from the GPS measurements. The second strategy, termed as external correction, involves independent path delay measurements. The present study is an integration of both techniques in which the parameter estimation as well as external correction are used to correct the path delay for $110{\sim}210$ km range baselines. Twenty-four parameters have been obtained in 24 hours solution by setting the cutoff angle at 3 and 15 degrees for parameter estimation strategy. Measurements from meteorological instruments and water vapor radiometer (WVR) are applied in the GPS data processing, separately, as an external strategy of present research work. Interesting results have been found, indicating more stable repeatability in baseline when the external correction strategy is applied especially with the inclusion of WVR observations. The offset of an order of 1 cm is found in the baselines determined by the two strategies. On the other hand, parameter estimation exhibits more stable in terms of GPS height repeatability. The offset in the GPS height determined by the two strategies is on the order of few centimeters.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1287-1300
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• 2017

Based on the observation that ignoring the angle dependency of multigroup resonance cross sections within a fuel pellet would result in nontrivial underestimation of the spatial self-shielding of flux, a parametrized spectral superhomogenization (SPH) factor library (PSSL) method is developed as a practical means of resolving the problem. Region-wise spectral SPH factors are calculated by the normal and transport corrected SPH iterations after ultrafine group slowing down calculations over various light water reactor pin-cell configurations. The parametrization is done with fuel temperature, U-238 number density, fuel radius, moderator source represented by ${\Sigma}_{mod}V_{mod}$, and the number density ratio of resonance nuclides to that of U-238 in a form of resonance interference correction factors. The parametrization is successful in that the root mean square errors of the interpolated SPH factors over the fuel regions of various pin-cells are within 0.1%. The improvement in reactivity error of the PSSL method is shown to be superior to that by the original SPH method in that the reactivity bias of -200 pcm to -300 pcm vanishes almost completely. It is demonstrated that the environment effect takes only about 4% in the reactivity improvement so that the pin-cell based PSSL method is effective in the assembly problems.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.29-39
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• 2015

This paper describes a design and implementation of fuzzy-based algorithm for hand-shake state detection and error compensation in the mobile optical image stabilization(OIS) motion detector. Since the gyro sensor output of the OIS motion detector includes inherent error signals, accurate error correction is required for prompt hand-shake error compensation and stable hand-shake state detection. In this research with a little computation overhead of fuzzy-based algorithm, the hand-shake error compensation could be improved by quickly reducing the angle and phase error for the hand-shake frequencies. Further, stability of the OIS system could be enhanced by the hand-shake states of {Halt, Little vibrate, Big vibrate, Pan/Tilt}, classified by subdividing the hand-shake angle. The performance and stability of the proposed algorithm in OIS motion detector is quantitatively and qualitatively evaluated with the emulated hand-shaking of ${\pm}0.5^{\circ}$, ${\pm}0.8^{\circ}$ vibration and 2~12Hz frequency. In experiments, the average error compensation gain of 3.71dB is achieved with respect to the conventional BACF/DCF algorithm; and the four hand-shake states are detected in a stable manner.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.2
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• pp.181-188
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• 2015

This paper present, the result of the guidance and control law for a course correction munitions(CCM) with 2sets of canards positioned in the rotating nose section. The nonlinear simulation model of the CCM was developed based on 7DOF equation of motion. The ability of correcting position was verified by open-loop control input with nonlinear model. The guidance and control command was constructed by reference trajectory which can be obtained with no control. Finally, the performance of the guidance and control law was evaluated through Monte-carlo simulation. The CEP(Circular Error Probability) was obtained by considering the errors in muzzle velocity, aerodynamic coefficient, wind, elevation and azimuth angle and density.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.22-30
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• 2023

When tracking small UAVs and drone targets in cloud clutter environments, MWIR sensors are often unable to track targets continuously. To overcome this problem, the SWIR sensor is mounted on the same gimbal. Target tracking uses sensor information fusion or selectively applies information from each sensor. In this case, parallax correction using the target distance is often used. However, it is difficult to apply the existing method to small UAVs and drone targets because the laser rangefinder's beam divergence angle is small, making it difficult to measure the distance. We propose a tracking method which needs not parallax correction of sensors. In the method, images from MWIR and SWIR sensors are captured simultaneously and a tracking error for gimbal driving is chosen by effectiveness measure. In order to prove the method, tracking performance was demonstrated for UAVs and drone targets in the real sky background using MWIR and SWIR image sensors.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.411-419
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• 2004

When the imaging object rotates in image plane during MRI scan, its rotation causes phase error and non-uniform sampling to MRI signal. The model of the problem including phase error non-uniform sampling of MRI signal showed that the MRI signals corrupted by rotations about an arbitrary center and the origin in image plane are different in their phases. Therefore the following methods are presented to improve the quality of the MR image which includes the artifact. The first, assuming that the angle of 2-D rotational motion is already known and the position of 2-D rotational center is unknown, an algorithm to correct the artifact which is based on the phase correction is presented. The second, in case of 2-D rotational motion with unknown rotational center and unknown rotational angle, an algorithm is presented to correct the MRI artifact. At this case, the energy of an ideal MR image is minimum outside the boundary of the imaging object to estimate unknown motion parameters and the measured energy increases when the imaging object has an rotation. By using this property, an evaluation function is defined to estimate unknown values of rotational angle at each phase encoding step. Finally, the effectiveness of this presented techniques is shown by using a phantom image with simulated motion and a real image with 2-D translational shift and rotation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.225-229
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• 2020

Recently, convolutional neural network (CNN) have been showed outstanding performance in the field of image recognition, image processing and computer vision, etc. In this paper, we propose a CNN-based image rotation correction algorithm as a solution to image rotation problem, which is one of the factors that reduce the recognition rate in image recognition system using CNN. In this paper, we trained our deep learning model with Leeds Sports Pose dataset to extract the information of the rotated angle, which is randomly set in specific range. The trained model is evaluated with mean absolute error (MAE) value over 100 test data images, and it is obtained 4.5951.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1360-1368
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• 2005

PDP is the flat panel display, suitable for high definition television because of large-sire and high-brightness. It has many advantages such as fast response, wide viewing angle, low weight, and simple manufacturing process for fabrication. However, there are some disadvantages and one of them is the image quality degradation, which is dependent on the digital signal processing. Although image quality of PDP is improving by many researches and experimentations, it still isn't as good as that of CRT because of various factors. One of them is worm-like pattern generated by an error diffusion process. And the worm-like pattern is severely increased after an APL process. An increased worm-like pattern occur a drop of resolution in image and a change of CCT according to each grayscale. In this paper, a method for improvement of image quality using the error diffusion which considers the APL process is proposed. In the proposed method, the APL process is performed before the error diffusion process. Simulation results showed that the proposed method has better performances for resolution in images and CCT uniformity according to each grayscale than the conventional method.