• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.219-222
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• 1994

This thesis describes an observer of Switched Reluctance Motor for position. velocity and torque estimation using current sening. Inductance of SRM varies trapezoidally with respect to the rotor position. This means that the inductance of each phase is a periodic function with the same period. Under this condition. the observer with a constant gain can be developed though SRM has nonlinear characteristics. Because SRM has equivalent physical meaning with each period. The stability of error system which is the difference between actual system and observer system. is analyzed using Lyapunov and variable structure theory. The effectiveness of the proposed estimation is shown by various simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.623-629
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• 2012

In this paper, we analysis the performance of position estimation when adopting Dynamic TDMA(DTDMA) in JTIDS RelNav. JTIDS RelNav is widely understood as a new navigation solution possibly capable to support or take cover of the role of conventional systems including INS or GPS no matter if they are working well or not. By maximizing the efficiency of radio resource management in MAC(Medium Access Control) layer we enhance the system performance without any replacement of hardware.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.417-420
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• 2005

In this paper proposes a very simple method to estimate the rotor position of a switched reluctance motor. By on-line estimating the self-inductance of the motor, the rotor position of the SR motor is obtained, and a closed-loop drive system can be achieved. Proposed methods can easy implement to application with sensorless SR motor drive system. Speed 2000rpm SR motor simulation executed with self inductance estimation and result represented. Simulation result verified the rotor position using the proposed self-inductance estimation method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1010-1018
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• 2009

An inertial navigation system for pedestrian position tracking is proposed, where the position is computed using inertial sensors mounted on shoes. Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it needs to reset errors frequently. During normal walking, there is an almost periodic zero velocity instance when a foot touches the floor. Using this fact, estimation errors are reduced and this method is called the zero velocity updating algorithm. When implementing this zero velocity updating algorithm, it is important to know when is the zero velocity interval. The gait states are modeled as a Markov process and each state is estimated using the hidden Markov model smoother. With this gait estimation, the zero or nearly zero velocity interval is more accurately estimated, which helps to reduce the position estimation error.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1166-1176
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• 2017

Estimation errors of the rotor speed and position in sensorless control systems of Permanent Magnet Synchronous Motors (PMSM) will lead to low efficiency and dynamic-performance degradation. In this paper, a parallel-type extended nonlinear observer incorporating the nominal parameters is constructed in the stator-fixed reference frame, with rotor position, speed, and the load torque simultaneously estimated. The stability of the extended nonlinear observer is analyzed using the indirect Lyapunov's method, and observer gains are selected according to the transfer functions of the speed and position estimators. Taking into account the parameter inaccuracies issue, explicit estimation error equations are derived based on the error dynamics of the closed-loop sensorless control system. An equivalent flux error is defined to represent the back Electromotive Force (EMF) error caused by the inaccurate motor parameters, and a compensation strategy is designed to suppress the estimation errors. The effectiveness of the proposed method has been validated through simulation and experimental results.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.73-74
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• 2018

This paper presents the incorporation of still-alive access points (SAPs) and helper access points (HAPs) that can be utilized as anchor nodes for position estimation of a First Responders (FRs) for rapidly deployable Emergency Communication Systems (ECS) in disaster recovery. In addition, the localization environment has is formulated and initially examines the use of a distributed Gauss-Newton algorithm (GNA) as optimization technizue. A simulation has been conducted and compared with the commonly used trilateration approach in position estimation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.871-872
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• 2009

FDP(Flight Data Processor) is processing of flight data for safety air traffic management. FDPs takes core function in aviation safety. Position estimation of aircraft is a key feature of the FDPs. In this paper, the requirements for position estimation of aircraft was defined.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1745-1753
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• 2004

A method of estimating the pose of a three-dimensional object from a set of two-dimensioal images based on parametric eigenspace method is proposed. A Gaussian blurred edge image is used as an input image instead of the original image itself as has been used previously. The set of input images is compressed using K-L transformation. By comparing the estimation errors for the original, blurred original, edge, and blurred edge images, we show that blurring with the Gaussian function and the use of edge images enhance the data compression ratio and decrease the resulting from smoothing the trajectory in the parametric eigenspace, thereby allowing better pose estimation to be achieved than that obtainable using the original images as it is. The proposed method is shown to have improved efficiency, especially in cases with occlusion, position shift, and illumination variation. The results of the pose angle estimation show that the blurred edge image has the mean absolute errors of the pose angle in the measure of 4.09 degrees less for occlusion and 3.827 degrees less for position shift than that of the original image.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1223-1231
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• 2009

We derive a systematic and iterative calibration algorithm, and position and pose estimation algorithm for the mobile robots in formation system based on the vision system. In addition, we develop a coordinate matching algorithm which calculates matched sequence of order in both extracted image coordinates and object coordinates for non interactive calibration and pose estimation. Based on the results of calibration, we also develop a camera simulator to confirm the results of calibration and compare the results of simulations with those of experiments in position and pose estimation.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.171-174
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• 2003

In this paper, we propose the method of stereo images composition using adaptive dense disparity estimation. For the correct composition of stereo image and 3D virtual object, we need correct marker position and depth information. The existing algorithms use position information of markers in stereo images for calculating depth of calibration object. But this depth information may be wrong in case of inaccurate marker tracking. Moreover in occlusion region, we can't know depth of 3D object, so we can't composite stereo images and 3D virtual object. In these reasons, the proposed algorithm uses adaptive dense disparity estimation for calculation of depth. The adaptive dense disparity estimation is the algorithm that use pixel-based disparity estimation and the search range is limited around calibration object.