• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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• pp.1294-1303
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• 2009

This paper presents a new numerical algorithm for fault discrimination and fault location estimation when occur to arcing ground and arcing line to line on transmission lines. The object of this paper is developed from new numerical algorithm to calculate the fault distance and simultaneously to make a distinction between transient and permanent faults. so the first of object for propose algorithm would be distinguish the permanent from the transient faults. This arcing fault discrimination algorithm is used if calculated value of arc voltage amplitude is greater than product of arc voltage gradient and the length of the arc path, which is equal or greater than the flashover length of a suspension insulator string[1-3]. Also, each algorithm is separated from short distance and long distance. This is difference to with/without capacitance between short to long distance. To test the validity of the proposed algorithms, the results of algorithm testing through various computer simulations are given. The test was simulated in EMTP/ATP simulator under a number of scenarios and calculate of algorithm was used to MATLAB.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.2
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• pp.94-101
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• 2009

We introduce a user authentication system using distance estimation and a simple challenge response protocol based on a pre-established key. Using the time difference of arrival between an RF signal and an ultrasonic signal, an authenticator verifies if a user's authentication token is within its threshold distance, and it also verifies if the token's response to its random challenge is valid. We implement our authentication system and we analyze the success rates for authentication according to the variations in the distances and facing angles between the authenticator and the token. Our experimental results show that the token is authenticated with very high probability in reasonable settings.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.108-116
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• 2008

In this paper, we propose an algorithm that can estimate the distance using disparity based on stereo vision system, even though the obstacle is located in long ranges as well as short ranges. We use sub-pixel interpolation to minimize quantization errors which deteriorate the distance accuracy when calculating the distance with integer disparity, and also we use enhanced adaptive fuzzy strong tracking Kalman filter(EAFSTKF) to improve the distance accuracy and track the path optimally. The proposed method can solve the divergence problem caused by nonlinear dynamics such as various vehicle movements in the conventional Kalman filter(CKF), and also enhance the distance accuracy and reliability. Our simulation results show that the performance of our method improves by about 13.5% compared to other methods in point of root mean square error rate(RMSER).

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.4
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• pp.447-455
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• 2018

If a hidden enemy is shooting, there is a threat against soldiers in recent conflicts. This paper aims to improve the localization of a muzzle using microphone array. Gunshot noise can provide information about the location of muzzle with two signals, the muzzle blast from the gun barrel and the projectile sound from the bullet. Two signals arrive to the microphone array with different arrival time and angle. If the arrival angles of the two signals are estimated, distance between sniper location and the microphone array can be calculated by using geometric principles. This method was established in 2003 by Pare. But this method has a limitation that it cannot calculate the distance when the arrival angles of the two signals are same. Also it has an error when the angle difference of arrival is small. In order to overcome this limitation, a new method is proposed that uses the change of characteristic of the projectile sound with respect to vertical distance from the trajectory. The proposed method estimates the distance correctly when the arrival angle of two signals are same, and when the angle difference between two signals is increased, the estimation error increases with respect to the angle. Therefore these two methods can be selected according to the angle difference between two signals to estimate the distance of the muzzle. Below the threshold of the angle difference, the proposed method can be used to estimate distance with smaller error than the existing method. This was demonstrated by shooting tests using actual sniper rifles.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.93-101
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• 1997

A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper proposes three object matching algorithm using robust HD measures based on M-estimation, least trimmed square (LTS), and .alpha.-trimmed mean methods, which are more efficient than the conventional HD measures. By computer simulation with synthetic and real images, the matching performance of the conventional HD smeasures and proposed' robust ones is compared.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.3
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• pp.219-226
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• 1992

In this study, Kalman filtering theory is applied to the estimation of symmetrical components from fault voltage and current signal when it comes to faults with the power system. An algorithm for estimating fault location accurately and quickly by calculating the symmetrical components from the extracted fundamental voltage phasor and current phasor is presented. Also, to confirm the validity of digital distance relaying techniques using Kalman filtering, the experimental results obtained by using the digital simulation of power system is shown.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.357-364
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• 2020

Indoor localization using an artificial marker plays a key role for a robot to be used in a service environment. A number of researchers have predefined the positions of markers and attached them to the positions in order to reduce the error of the localization method. However, it is practically impossible to attach a marker to the predetermined position accurately. In order to visualize the position of an object in the environment based on the marker attached to them, it is necessary to consider a change of marker's position or the addition of a marker because of moving the existed object or adding a new object. In this paper, we studied the method to estimate the artificial marker's global position for the visualization of environment. The system calculates the relative distance from a reference marker to others repeatedly to estimate the marker's position. When the marker's position is changed or new markers are added, our system can recognize the changed situation of the markers. To verify the proposed system, we attached 12 markers at regular intervals on the ceiling and compared the estimation result of the proposed method and the actual distance. In addition, we compared the estimation result when changing the position of an existing marker or adding a new marker.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.677-682
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• 2010

This paper addresses a method of estimating roughly the human pose by comparing Haar-wavelet value which is learned in face detection technology using AdaBoost algorithm. We also presents its application to face recognition. The learned weak classifier is used to a Haar-wavelet robust to each pose's feature by comparing the coefficients during the process of face detection. The Mahalanobis distance is used to measure the matching degree in Haar-wavelet selection. When a facial image is detected using the selected Haar-wavelet, the pose is estimated. The proposed pose estimation can be used to improve face recognition speed. Experiments are conducted to evaluate the performance of the proposed method for pose estimation.

• Earthquakes and Structures
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• v.26 no.2
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• pp.117-130
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• 2024

Probabilistic model of seismic demand is the main tool used for seismic demand estimation, which is a fundamental component of the new performance-based design method. This model seeks to mathematically relate the seismic demand parameter and the ground motion intensity measure. This study is intended to use Bayesian analysis to evaluate the accuracy of the seismic demand estimation of Steel moment resisting frames (SMRFs) through a completely Bayesian method in statistical calculations. In this study, two types of intensity measures (earthquake intensity-related indices such as magnitude and distance and intensity indices related to ground motion and spectral response including peak ground acceleration (PGA) and spectral acceleration (SA)) have been used to form the models. In addition, an extensive database consisting of sixty accelerograms was used for time-series analysis, and the target structures included five SMRFs of three, six, nine, twelve and fifteen stories. The results of this study showed that for low-rise frames, first mode spectral acceleration index is sufficient to accurately estimate demand. However, for high-rise frames, two parameters should be used to increase the accuracy. In addition, adding the product of the square of earthquake magnitude multiplied by distance to the model can significantly increase the accuracy of seismic demand estimation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.251-258
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• 2004

This paper proposes a method for estimating the illuminant chromaticity using the distributions of the camera responses obtained by a CCD camera in a real-world scene. Illuminant estimation using a highlight method is based on the geometric relation between a body and its surface reflection. In general, the pixels in a highlight region are affected by an illuminant geometric difference, camera quantization errors, and the non-uniformity of the CCD sensor. As such, this leads to inaccurate results if an illuminant is estimated using the pixels of a CCD camera without any preprocessing. Accordingly, to solve this problem the proposed method analyzes the distribution of the CCD camera responses and selects pixels using the Mahalanobis distance in highlight regions. The use of the Mahalanobis distance based on the camera responses enables the adaptive selection of valid pixels among the pixels distributed in the highlight regions. Lines are then determined based on the selected pixels with r-g chromaticity coordinates using a principal component analysis(PCA). Thereafter, the illuminant chromaticity is estimated based on the intersection points of the lines. Experimental results using the proposed method demonstrated a reduced estimation error compared with the conventional method.