• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.177-180
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• 2001

This paper describes the calibration method and the evaluation method of relative expanded uncertainty for a multi-axis force/moment sensor. This sensor should be calibrated to be use in the industry. Now, the confidence of the calibration result is expressed with interference error. But it is no inaccurate, because an interference error, besides, a reproducibility error of the sensor, a error of this six-axis force/moment sensor calibrator, and so on. Thus, in order to accurately evaluate the relative expanded uncertainty of it, the concept of the uncertainty should be induced, and these errors must be contained in the relative expanded uncertainty. In this paper, the calibration method is exhibited and the evaluation method of the relative expanded uncertainty is also exhibited. And, a six-axis force/moment sensor was calibrated and the relative expanded uncertainty was evaluated.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.357-366
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• 2020

This paper addressed a relative navigation method for autonomous rendezvous and docking of cube-satellites using single frequency Differential GPS (DGPS) under the intermittent communication between satellites. Since the ionospheric error of GPS measurement is variable depending on the visible satellites, a few meters error of relative navigation is occurred in the Low-Earth Orbit (LEO) environment. Therefore, it is essential to remove the ionospheric error to perform relative navigation. Besides, an intermittent communication period for receiving GPS measurements of the target satellite is limited for getting information every sampling time. To solve this problem, a method combining range domain DGPS and orbit propagation is proposed in this paper. The proposed method improves the performance of DGPS by using Hatch filter and solves an intermittent communication problem by estimating the relative position and velocity using Hill-Clohessy-Wiltshire Equation. Through the simulation, it is verified that the suggested algorithm provides the relative position error within RMS 0.5 m and the relative velocity error within RMS 3 cm/s. Furthermore, it has the advantage that it is suitable for real-time implementation using single-frequency GPS measurements and is computationally efficient.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.697-710
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• 2021

Relative error prediction is preferred over ordinary prediction methods when relative/percentile errors are regarded as important, especially in econometrics, software engineering and government official statistics. The relative error prediction techniques have been developed in linear/nonlinear regression, nonparametric regression using kernel regression smoother, and stationary time series models. However, random effect models have not been used in relative error prediction. The purpose of this article is to extend relative error prediction to some of generalized linear mixed model (GLMM) with panel data, which is the random effect models based on gamma, lognormal, or inverse gaussian distribution. For better understanding, the real auto insurance data is used to predict the claim size, and the best predictor and the best relative error predictor are comparatively illustrated.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.994-1000
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• 2003

A new relative motion control methodology for a following system to an independent leading system is proposed for controlling relative position, velocity, and tension etc. It is based on maintaining minimum relative error between two independent systems. The control command of the following system to a leading system is generated by adding the current command and the output of the relative error compensation. The proposed control method is implemented on the experimental equipment which is a wire winding-unwinding system to control the tension of the line. The results show the unwinding system(follower) following the independent motion of the winding system(leader) to control the constant tension of the line in order to keep the roller dancer in reference position. The relative motion control method proposed in this paper can be applied to high precision equipment for unwinding and winding fine wire, fine fiber, and tape etc.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.24-36
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• 2011

A new approach for spacecraft absolute attitude estimation based on the unscented Kalman filter (UKF) is extended to relative attitude estimation and navigation. This approach for nonlinear systems has faster convergence than the approach based on the standard extended Kalman filter (EKF) even with inaccurate initial conditions in attitude estimation and navigation problems. The filter formulation employs measurements obtained from a vision sensor to provide multiple line(-) of(-) sight vectors from the spacecraft to another spacecraft. The line-of-sight measurements are coupled with gyro measurements and dynamic models in an UKF to determine relative attitude, position and gyro biases. A vector of generalized Rodrigues parameters is used to represent the local error-quaternion between two spacecraft. A multiplicative quaternion-error approach is derived from the local error-quaternion, which guarantees the maintenance of quaternion unit constraint in the filter. The scenario for bounded relative motion is selected to verify this extended application of the UKF. Simulation results show that the UKF is more robust than the EKF under realistic initial attitude and navigation error conditions.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.477-483
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• 2015

This study deals with the decision problem of sample size by the relative standard error of estimates derived from survey results in successive occasions. The population of the construction in business survey results is used to calculate quartile of the relative standard error of the 1,000 sample obtained from simple or stratified random sampling. The sample size at time t with a relative standard error of the point (t-1) in the successive occasions were calculated according to the sampling method. As a result, in terms of the sample size according to the size of the relative standard error of the (t-1), simple random sampling differs significantly from stratified sampling. In addition, we could see differences in sample size (depending on how the population is stratified) and that careful attention is required in the problem of sample size by the relative standard error of estimates derived from survey results in successive occasions.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.3
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• pp.5-11
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• 2002

This paper describes the methods for calibration and evaluation of the relative expanded uncertainty of a multi-axis force/moment sensor. In order to use the sensor in the industry, it should be calibrated and its relative expanded uncertainty should be also evaluated. At present, the confidence of the sensor is shown with only interference error. However, it is not accurate, because the calibrated multi-axis force/moment sensor has an interference error as well as a reproducibility error of the sensor, etc. In this paper, the methods fur calibration and for evaluation of the relative expanded uncertainty of a multi-axis force/moment sensor are newly proposed. Also, a six-axis force/moment sensor is calibrated with the proposed calibration method and the relative expanded uncertainty is evaluated using the proposed uncertainty evaluation method and the calibration results. It is thought that the methods fur calibration and evaluation of the uncertainty can be usually used for calibration and evaluation of the uncertainty of the multi-axis force/moment sensor.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.66-72
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• 1999

Robot calibration is very important to improve the accuracy of robot manipulators. However, the calibration procedure is very time consuming and laborious work for users. In this paper, we propose a method of relative error compensation to make the calibration procedure easier. The method is completed by a Pi-Sigma network architecture which has sufficient capability to approximate the relative relationship between the accuracy compensations and robot configurations while maintaining an efficient network learning ability. By experiment of 4-DOF SCARA robot, KIRO-3, it is shown that both the error of joint angles and the positioning error of end effector are drop to 15$\%$. These results are similar to those of other calibration methods, but the number of measurement is remarkably decreased by the suggested compensation method.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.315-324
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• 2002

For estimating the error variance under the relative squared error loss in two-way analysis of variance models, we provide a class of hierarchical Bayes estimators and then derive a subclass of the hierarchical Bayes estimators, each member of which dominates the best multiple of the error sum of squares which is known to be minimax. We also identify a subclass of non-minimax hierarchical Bayes estimators.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.1
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• pp.118-128
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• 2017

In this study, we propose a real time inertial navigation system/global positioning system (INS/GPS) integrated smoothing algorithm based on an extended Kalman filter (EKF) and a position damping loop (PDL) for synthetic aperture radar (SAR). Integrated navigation algorithms usually induce discontinuities due to error correction update by the Kalman filter, which are as detrimental to the performance of SAR as the relative position error. The proposed smoothing algorithm suppresses these discontinuities and also reduces the relative position error in real time. An EKF estimates the navigation errors and sensor biases, and all the errors except for the position error are corrected directly and instantly. A PDL activated during SAR operation period imposes damping effects on the position error estimates, where the estimated position error is corrected smoothly and gradually, which contributes to the real time smoothing and small relative position errors. The residual errors are re-estimated by the EKF to maintain the estimation performance and the stability of the overall loop. The performance improvements were confirmed by Monte Carlo simulations. The simulation results showed that the discontinuities were reduced by 99.8% and the relative position error by 48% compared with a conventional EKF without a smoothing loop, thereby satisfying the basic performance requirements for SAR operation. The proposed algorithm may be applicable to low cost SAR systems which use a conventional INS/GPS without changing their hardware configurations.