• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.6
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• pp.57-64
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• 2000

In order to regulate cutting torque in milling, monitoring system should be set to a certain threshold. Radial immersion ratio is an important factor to determine the threshold and should be estimated in process for automatic regulation. In this paper, on-line estimation of the radial immersion ratio using spindle motor current in face milling is presented. When a tooth finishes sweeping, a sudden drop of cutting torque occurs. This torque drop is equal to the cutting torque acting on a single tooth at the swept angle of cut and can be acquired from cutting torque signals. Average cutting torque per revolution can also be calculated from cutting torque signals. The ratio of cutting torque acting on a single tooth at the swept angle of cut to the average cutting torque per revolution is a function of the swept angle of cut and the number of teeth. Using the magnitude of this ratio, the radial immersion ratio is estimated. Identical algorithm is adopted to estimate the immersion ratio based on the spindle motor current measurement. The experiments performed under different cutting conditions show that the radial immersion ratio can be estimated within 10% error range by the proposed method using spindle motor current. Varying immersion ratio is also estimated well using the presented algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.248-254
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• 2013

In location finding system using spaced multi-sensor, there is the phenomenon that the position estimation accuracy is degraded by the location of signal sources and the sensors. This phenomenon is called GDOP(Geometric Dilution Of Precision) effect. and to minimize these effects, research is needed on how. In this paper, I will describe how to minimize GDOP effect, estimating possibility of GDOP using AOA(angle of arrival) information of spaced multi sensors, and removing sensor error factor in position estimation.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.487-499
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• 2009

Atmospheric correction of satellite measurements is a major step to estimate accurate surface reflectance of solar spectrum channels. In this study, Simplified Method for the Atmospheric Correction (SMAC) radiative transfer model used to retrieve surface reflectance from MODIS (MODerate resolution Imaging Spectrometer) top of atmosphere (TOA) reflectance. It is fast and simple atmospheric correction method, so it uses for work site operation in various satellite. This study attempts a test of accuracy of SMAC through a sensitivity test to detected error sources and to improve accuracy of surface reflectance using SMAC. The results of SMAC as compared with MODIS surface reflectance (MOD09) was represented that low accuracy ($R^2\;=\;0.6196$, Root Means Square Error (RMSE) = 0.00031, bias = - 0.0859). Thus sensitivity analysis of input parameters and coefficients was conducted to searching error sources. Among the input parameters, Aerosol Optical Depth (AOD) is the most influence input parameter. In order to modify AOD term in SMAC code, Stepwise multiple regression was performed with testing and remove variable in three stages with independent variables of AOD at 550nm, solar zenith angle, viewing zenith angle. Surface reflectance estimation by using Newly proposed AOD term in the study showed that improve accuracy ($R^2\;=\;0.827$, RMSE = 0.00672, bias = - 0.000762).

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.149-156
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• 2014

A magnetic compass module must be calibrated accurately before use. Moreover, the calibration process must be performed taking into account any magnetic dip if the magnetic compass module has tilt angles. For this, a calibration method for a magnetic compass module is explained. Tilt error of the magnetic compass module is compensated using a biaxial accelerometer generally. The accelerometer error causes a tilt angle calculation error that gives rise to an azimuth calculation error. For error property analysis, error equations are derived and simulations are performed. In the simulation results, the accuracy of derived error equations is verified. If a biaxial magnetic compass module is used instead of a triaxial one, the magnetic dip and z-axis magnetic compass data must be estimated for tilt compensation. Lastly, estimation equations for the magnetic dip and z-axis magnetic compass data are derived, and the performance of the equations is verified based on a simulation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.137-144
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• 2009

This paper deals with the performance comparison of jammer signal's angle spreading in the beamforming after the estimation of direction of arrival using 3D array antenna basis of the GPS signal. After the estimation of direction of arrival using array antenna, the beamforming is need for the direction of arrival by spatial filtering and the other direction are nulling for reducing intererence signal, it is possible to improving the received signal strength and quality. But we obtains the degraded performance by the angle spreading due to the multi-jammer signal in this process. In this paper, the MUSIC and LCMV algorithms are applied for the estimating the direction of arrival and for beamforming using the 5 types of 3D array antenna. we performs the comparison of performance by calculating the bit error rate applying the BPSK modem and the varying the azimuth and elevation angle of incoming jammer signal. As a result of simulation, the Curved (B) type 3D array antenna has a more better performance compared to the other type antenna.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.395-400
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• 2008

This paper relates to the performance analysis of DoA estimation algorithm in 2-dimensional circular array antenna for the receiving of GPS signal which is used for the performance improvement by elimination of jammer signal. By performing the spatial filtering after the DoA estimation in array antenna, the quality of receiving signal can improve by the nulling of jammer signal from the undesired direction and the forming of beam from the desired direction. In this paper, the MUSIC and MinNorm algorithm used for DoA estimation were applied after fixing the angle and power of jammer signal in 4 element and 7 element circular array antenna. In order to performance analysis, the estimation result and estimation error were computed by computer simulation. As a result, the MUSIC and MinNorm were fairly good in azimuth and elevation angle estimation of DoA in case of good signal to noise ratio and the MUSIC has better performance compared to MinNorm in case of poor signal to noise ratio.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.126-131
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• 2012

Tire force is one of important parameters which determine vehicle dynamics. However, it is hard to measure tire force directly through sensors. Not only the sensor is expensive but also installation of sensors on harsh environments is difficult. Therefore, estimation algorithms based on vehicle dynamic models are introduced to estimate the tire forces indirectly. In this paper, an estimation system for estimating lateral force and states is suggested. The state-space equation is constructed based on the 3-DOF bicycle model. Extended Kalman Filter, Unscented Kalman Filter and Ensemble Kalman Filter are used for estimating states on the nonlinear system. Performance of each algorithm is evaluated in terms of RMSE (Root Mean Square Error) and maximum error.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.5
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• pp.402-409
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• 2015

This paper proposes a novel rotor position error calculation method for high-frequency signal-injected sensorless control. The rotor position error using the conventional modulation method can be only measured up to ${\pm}45^{\circ}$. In addition, when the rotor position estimation error is not sufficiently small, the small angle approximation in no longer valid. To overcome these problems, this study introduces a new rotor position error calculation method using the rotating matrix. In this study, the position error measurement range of the proposed method is extended from ${\pm}45^{\circ}$ to ${\pm}90^{\circ}$. The linearity between the real rotor position error and the estimated error is maintained by nearly $90^{\circ}$. These features of the proposed method improve the performance of the sensorless control. The validity of the proposed method is verified by simulations and experiments.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.123-126
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• 1997

We present a method for the estimation of 3D solid angle assessment of the acetabular coverage of the femoral head in 3D space. At first, femoral head and acetabulum is segmented from the original CT scan images. The slice thickness is 1.5mm and the number of slices is usually 30-40 to cover the entire acetabulum. The superior half of the femoral head is modeled as part of a sphere. Thus, the axial cross sections of the upper half of the femoral head are also modeled as circles. A set of points from each outline image of femoral head is fitted recursively into a circle by minimizing root-mean-square (RMS) error. With these fitted circles, a center point of the femoral head model is evaluated. This is a reference point for calculating the solid angle of the acetabular inner surface. Next, the tangent lines connecting from a set of points of the acetabular edge to the center of the fitted sphere are obtained. The lines pass through the unit sphere whose center is the same as that of the femoral head. With the points on the unit sphere, we calculate area and estimate the solid angle. Based on this solid angle, the deformity of the acetabulum is analyzed. In case of normal subject, the solid angle is about 4.3 (rad) and acetabular coverage is 68%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.31-40
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• 2003

Most face recognition systems are based on 2D images and applied in many applications. However, it is difficult to recognize a face when the pose varies severely. Therefore, head pose estimation is an inevitable procedure to improve recognition rate when a face is not frontal. In this paper, we propose a novel head pose estimation algorithm for 3D face recognition. Given the 3D range image of an unknown face as an input, we automatically extract facial feature points based on the face curvature. We propose an Error Compensated Singular Value Decomposition (EC-SVD) method based on the extracted facial feature points. We obtain the initial rotation angle based on the SVD method, and perform a refinement procedure to compensate for remained errors. The proposed algorithm is performed by exploiting the extracted facial features in the normaized 3D face space. In addition, we propose a 3D nearest neighbor classifier in order to select face candidates for 3D face recognition. From simulation results, we proved the efficiency and validity of the proposed algorithm.