• Journal of applied mathematics & informatics
• /
• 제7권1호
• /
• pp.237-245
• /
• 2000

In this paper, we consider to the adjustment weighting procedure in the two phase sampling scheme. In general, the unit nonresponses may be occured in the final survey operation. When the unit nonresponse be generated in survey, it is able to use the auxiliary variable for estimating of interest variable. In this viewpoint, we use the two kinds level of auxiliary variable, $X_{1k}$ and $X_{2k}$ for the calibration procedure. We proprose the two-step Newton's method in the calibration estimation procedure for the two phase sampling.

• International Journal of Control, Automation, and Systems
• /
• 제2권4호
• /
• pp.536-541
• /
• 2004

It is important to estimate and calibrate sensor errors in maintaining the performance level of SDINS. In this study, an estimation technique of fixed sensor errors for SDINS calibration is discussed. First, the fixed errors of gyros and accelerometers, excluding gyro biases are estimated by the navigation information of SDINS in multi-position. The SDINS with RLG includes flexure errors. In this study, the gyros flexures are out of consideration, but the proposed procedure selects certain positions and rotations in order to minimize the influence of flexures. Secondly, the influences of random walks, flexures and orientation errors are verified via numerical simulations. Thirdly, applying the previous estimated errors to SDINS, the estimation of gyro biases is conducted via the additional control signals of close-loop self-alignment. Lastly, the experiments illustrate that the extracted calibration parameters are available for the improvement of SDINS.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 1990년도 춘계공동학술대회논문집; 한국과학기술원; 28 Apr. 1990
• /
• pp.254-262
• /
• 1990

A predictive functional relationship model is presented for the calibration problem in which the standard as well as the nonstandard measurements are subject to error. For the estimation of the relationship between the two measurements, the ordinary least squares and maximum likelihood estimation methods are considered, while for the prediction of unknown standard measurementswe consider direct and inverse approaches. Relative performances of those calibration procedures are compared in terms of the asymptotic mean square error of prediction.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2006년도 학술발표회 논문집
• /
• pp.643-646
• /
• 2006

An operational calibration is applied to improve radar rainfall intensity using rainfall obtained from rain gauge. The method is applied under the assumption of the temporal continuity of rainfall, the rainfall intensity from rain gauge is linearly related to that from radar. The method is applied to the cases of typhoon and rain band using the reflectivity of CAPPI at 1.5km obtained from Jindo radar. The CAPPI is obtained by bilinear interpolation. For the two cases, the rainfall intensities obtained by operational calibration are very consistent with the ones by the rain gauges. The present study shows that the correlation between the rainfall intensity by operational calibration and rain gauges is better than the one between the rainfall intensity by M-P relationship and rain gauges. The correlation coefficients between the total rainfall intensity obtained by operational calibration and rain gauges in typhoon and rain band cases are 0.99 and 0.97, respectively. Areal rainfalls are estimated using the field of calibration factor interpolated by Barnes objective analysis. The method applied here shows an improvement in the areal rainfall estimation. For the cases of typhoon and rain band, the correlation between the areal rainfall by operational calibration and rain gauges is better than the one between the area rainfall by M-P relationship and rain gauges. The correlation coefficients between the areal rainfall obtained by operational calibration and rain gauges in typhoon and rain band cases are 0.97 and 0.84, respectively. The present study suggests that the operational calibration is very useful for the real-time estimation of rainfall intensity and areal rainfall.

• 로봇학회논문지
• /
• 제15권4호
• /
• pp.350-356
• /
• 2020

Workers have been replaced by mobile manipulators for factory automation in recent years. One of the typical tasks for automation is that a mobile manipulator moves to a target location and picks and places an object on the worktable. However, due to the pose estimation error of the mobile platform, the robot cannot reach the exact target position, which prevents the manipulator from being able to accurately pick and place the object on the worktable. In this study, we developed an automatic alignment system using a low-cost camera mounted on the end-effector of a collaborative robot. Camera calibration and pose estimation methods were also proposed for the automatic alignment system. This algorithm uses a markerboard composed of markers to calibrate the camera and then precisely estimate the camera pose. Experimental results demonstrate that the mobile manipulator can perform successful pick and place tasks on various conditions.

• 대한산업공학회지
• /
• 제19권2호
• /
• pp.35-41
• /
• 1993

Statistical calibration is a useful technique for achieving compatibility between two different measurement methods, and it usually consists of two steps : (1) estimation of the relationship between the standard and nonstandard measurements, and (2) prediction of future standard measurements using the estimated relationship and observed nonstandard measurements. A predictive multivariate errors-in-variables model is presented for the multivariate calibration problem in which the standard as well as the nonstandard measurements are subject to error. For the estimation of the relationship between the two measurements, the maximum likelihood (ML) estimation method is considered. It is shown that the direct and the inverse predictors for the future unknown standard measurement are the same under ML estimation. Based upon large-sample approximations, the mean square error of the predictor is derived.

• Journal of applied mathematics & informatics
• /
• 제8권3호
• /
• pp.975-987
• /
• 2001

We treat the problem of variance estimation for the estimator of population total, which is derived from the calibration estimation procedure corresponding to the levels of auxiliary information under nonresponse situation. We develop the calibrated variance estimation procedure using the fact that the population total and variance as well as the sample total and variance of the auxiliary variable are known. We show that the proposed variance estimation procedure improves the $Lundst\ddot{o}rm$ and $S\ddot{a}rndal's$ (1999) procedure with respect to the variance and nonresponse bias reduction through the simulation study.

• 센서학회지
• /
• 제26권4호
• /
• pp.259-265
• /
• 2017

Magnetometer calibration must be performed before the use of three-axis magnetometers to ensure the accuracy of orientation estimation. Recently, one of the most popular calibration approaches is the ellipsoid fitting technique due to its high performance in calibration. To date, in fact, performances of the existing ellipsoid fitting methods have been evaluated with full range rotation data. However, in case of the calibration of magnetometers attached to vehicles, ships, and planes, it is very difficult to collect the full range rotation data since their allowable ranges in terms of roll and pitch are limited to small. This constraint may result in serious performance degradation of some ellipsoid fitting algorithms. Therefore, to be practical, this paper proposes a weighted least square-based magnetometer calibration method that is robust in roll-pitch limited conditions. Furthermore, the proposed method is a linear approach and thus is free from the well-known initial value issue in nonlinear approaches. Experimental results show the superiority of the proposed method to other ellipsoid-fitting calibration methods.

• Nuclear Engineering and Technology
• /
• 제50권1호
• /
• pp.203-210
• /
• 2018

As the modernization of the nuclear instrumentation system progresses, research reactors have adopted digital wide-range neutron power measurement (DWRNPM) systems. These systems typically monitor the neutron flux across a range of over 10 decades. Because neutron detectors only measure the local neutron flux at their position, the local neutron flux must be converted to total reactor power through calibration, which involves mapping the local neutron flux level to a reference reactor power. Conventionally, the neutron power range is divided into smaller subranges because the neutron detector signal characteristics and the reference reactor power estimation methods are different for each subrange. Therefore, many factors should be considered when preparing the calibration procedure for DWRNPM channels. The main purpose of this work is to serve as a reference for performing the calibration of DWRNPM systems in research reactors. This work provides a comprehensive overview of the calibration of DWRNPM channels by describing the configuration of the DWRNPM system and by summarizing the theories of operation and the reference power estimation methods with their associated calibration procedure. The calibration procedure was actually performed during the commissioning of an open-pool type research reactor, and the results and experience are documented herein.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.527-530
• /
• 1996

The Kalman filter has been used as a self-localization method for the mobile robot. To satisfy the assumptions inherent in the Kalman filter, we should calibrate the sensors of the robot before use of them. However, it is generally hard to find exact sensor parameters, and the parameters may change during the robot task as the environment varies. Thus we need to perform on-line sensor calibration, by which we can obtain more credible location of the mobile robot. In this paper, we present an on-line sensor calibration scheme which estimates the unknown sensor bias and the current position of the robot. To this end, first we find out the calibration errors of the sensor from redundant sensory data using the parity vector and recursive minimum variance estimation. Then we calculate the current position of the robot by weighted least square estimation without internal encoder data. The performance of the proposed method is evaluated through computer simulation.