• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.227-233
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• 2018

This study presents the generation and accuracy assessment of predicted orbital ephemeris based on satellite laser ranging (SLR) for geostationary Earth orbit (GEO) satellites. Two GEO satellites are considered: GEO-Korea Multi-Purpose Satellite (KOMPSAT)-2B (GK-2B) for simulational validation and Compass-G1 for real-world quality assessment. SLR-based orbit determination (OD) is proactively performed to generate orbital ephemeris. The length and the gap of the predicted orbital ephemeris were set by considering the consolidated prediction format (CPF). The resultant predicted ephemeris of GK-2B is directly compared with a pre-specified true orbit to show 17.461 m and 23.978 m, in 3D root-mean-square (RMS) position error and maximum position error for one day, respectively. The predicted ephemeris of Compass-G1 is overlapped with the Global Navigation Satellite System (GNSS) final orbit from the GeoForschungsZentrum (GFZ) analysis center (AC) to yield 36.760 m in 3D RMS position differences. It is also compared with the CPF orbit from the International Laser Ranging Service (ILRS) to present 109.888 m in 3D RMS position differences. These results imply that SLR-based orbital ephemeris can be an alternative candidate for improving the accuracy of commonly used radar-based orbital ephemeris for GEO satellites.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.92.1-92.1
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• 2012

In this work we have examined the performance of the WSA/ENLIL cone model provided by Community Coordinated Modeling Center (CCMC). The WSA/ENLIL model simulates the propagation of coronal mass ejections (CMEs) from the Sun into the heliosphere. We estimate the shock arrival times at the Earth using 29 halo CMEs from 2001 to 2002. These halo CMEs have cone model parameters from Michalek et al. (2007) as well as their associated interplanetary (IP) shocks. We make a comparison between CME arrival times by the WSA/ENLIL cone model and IP shock observations. For the WSA/ENLIL cone model, the root mean square(RMS) error is about 13 hours and the mean absolute error(MAE) is approximately 10.4 hours. We compared these estimates with those of the empirical model by Kim et al.(2007). For the empirical model, the RMS and MAE errors are about 10.2 hours and 8.7 hours, respectively. We are investigating several possibilities on relatively large errors of the WSA/ENLIL cone model, which may be caused by cone model velocities, CME density enhancement factor, or CME-CME interaction.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.2
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• pp.168-177
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• 2003

The performance sensitivity analysis due to manufacturing/alignment errors is performed for the Ku-band offset parabola antenna of the domestic Communications and Broadcasting Satellite. The performance variations due to reflector random surface error, which inevitably happens during reflector manufacturing, are statistically analyzed using RMS error and correlation interval. The impact on the antenna performance of the fred hem's position and angular errors is investigated, and the sensitive directions are identified. When the target tolerances are applied, the performance degradations are found to be within the loss budget or corresponding performance margins.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.355-362
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• 2012

The aim of this study was to develop a bundle position-wise linear model (BPLM) to predict Pressure Tube (PT) diametral creep employing the previously measured PT diameters and operating conditions. There are twelve bundles in a fuel channel, and for each bundle a linear model was developed by using the dependent variables, such as the fast neutron fluences and the bundle coolant temperatures. The training data set was selected using the subtractive clustering method. The data of 39 channels that consist of 80 percent of a total of 49 measured channels from Units 2, 3, and 4 of the Wolsung nuclear plant in Korea were used to develop the BPLM. The data from the remaining 10 channels were used to test the developed BPLM. The BPLM was optimized by the maximum likelihood estimation method. The developed BPLM to predict PT diametral creep was verified using the operating data gathered from Units 2, 3, and 4. Two error components for the BPLM, which are the epistemic error and the aleatory error, were generated. The diametral creep prediction and two error components will be used for the generation of the regional overpower trip setpoint at the corresponding effective full power days. The root mean square (RMS) errors were also generated and compared to those from the current prediction method. The RMS errors were found to be less than the previous errors.

• Ocean and Polar Research
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• v.30 no.2
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• pp.129-140
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• 2008

As a preliminary effort to establish a data assimilative ocean forecasting system, we reviewed the theory of the Ensemble Kamlan Filter (EnKF) and developed practical techniques to apply the EnKF algorithm in a real ocean circulation modeling system. To verify the performance of the developed EnKF algorithm, a wind-driven double gyre was established in a rectangular ocean using the Regional Ocean Modeling System (ROMS) and the EnKF algorithm was implemented. In the ideal ocean, sea surface temperature and sea surface height were assimilated. The results showed that the multivariate background error covariance is useful in the EnKF system. We also tested the sensitivity of the EnKF algorithm to the localization and inflation of the background error covariance and the number of ensemble members. In the sensitivity tests, the ensemble spread as well as the root-mean square (RMS) error of the ensemble mean was assessed. The EnKF produces the optimal solution as the ensemble spread approaches the RMS error of the ensemble mean because the ensembles are well distributed so that they may include the true state. The localization and inflation of the background error covariance increased the ensemble spread while building up well-distributed ensembles. Without the localization of the background error covariance, the ensemble spread tended to decrease continuously over time. In addition, the ensemble spread is proportional to the number of ensemble members. However, it is difficult to increase the ensemble members because of the computational cost.

• Korean Journal of Optics and Photonics
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• v.27 no.3
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• pp.106-113
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• 2016

In this paper, we deal with the wavefront compensation capability of a silicon carbide (SiC) deformable mirror (DM) with 37 actuators for adaptive optics. The wavefront compensation capability of the SiC DM is predicted by computer simulation and examined by actual experiments with a closed-loop adaptive optics system consistsing of a light source, a phase plate, a SiC DM, a high speed Shack-Hartmann sensor, and a control computer. Distortion of wavefront is caused by the phase plate in the closed-loop adaptive optics system. The distorted wavefront has a peak-to-valley (PV) wavefront error of $0.3{\mu}m{\sim}0.9{\mu}m$ and root-mean-square (RMS) error of $0.06{\mu}m{\sim}0.25{\mu}m$. The high-speed Shack-Hartmann sensor measures the wavefront error of the distortion caused by the phase plate, and the SiC DM compensates for the distorted wavefront. The compensated wavefront has residual errors lower than $0.1{\mu}m$ PV and $0.03{\mu}m$ RMS. Consequently, we conclude that we can compensate for the distorted wavefront using the SiC DM in the closed-loop adaptive optics system with an operating frequency speed of 500 Hz.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.28.3-28.3
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• 2011

Halo coronal mass ejections (HCMEs) are mainly responsible for the most severe geomagnetic storms. To minimize the projection effect of the HCMEs observed by coronagraphs, several cone models have been suggested. These models allow us to determine the geometrical and kinematic parameters of HCMEs : radial speed, source location, angular width, and the angle between the central axis of the cone and the plane of the sky. In this study, we compare these parameters form two representative cone models (the ice-cream cone model and the asymmetric cone model) using well-observed HCMEs from 2001 to 2002. And we obtain the root mean square error (rms error) between observed projection speeds and calculated projection speeds for both cone models. It is found that the average rms speed error (89 km/s) of the asymmetric cone model is a little smaller than that (107 km/s) of the ice-cream cone models, implying that the radial speeds from both models are reasonably estimated. We also find that the radial speeds obtained from two models are similar to each other with the correlation coefficient of about 0.8.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.96.1-96.1
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• 2011

Halo coronal mass ejections (HCMEs) are major cause of the geomagnetic storms. To minimize the projection effect by coronagraph observations, we consider two CME cone models: an ice-cream cone model and an asymmetric cone model. These models allow us to determine three dimensional parameters of HCMEs such as radial speed, angular width, and the angle between sky plane and cone axis. In this study, we compare these parameters obtained from both models using 50 well-observed HCMEs from 2001 to 2002. Then we obtain the root mean square error (RMS error) between measured projection speeds and estimated ones for the models. As a result, we find that the radial speeds obtained from the models are well correlated with each other (R=0.89), and the correlation coefficient of angular width is 0.68. The correlation coefficient of the angle between sky plane and cone axis is 0.42, which is much smaller than what is expected. The reason may be due to the fact that the source locations of the asymmetric cone model are assumed to be near the center. The average RMS error of the asymmetric cone model (86.2km/s) is slightly smaller than that of the ice-cream cone model (88.6km/s).

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.469-475
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• 2015

This paper describes about the method for designing an extended Kalman filter to accurately measure the position of the spatial-phase system using a semiconductor sensor. Spatial position is expressed by the correlation of the rotated coordinate system attached to the body from the inertia coordinate system (a fixed coordinate system). To express the attitude, quaternion was adapted as a state variable, Then, the state changes were estimated from the input value which was measured in the gyro sensor. The observed data is the value obtained from the acceleration sensor. By matching between the measured value in the acceleration sensor and the predicted calculation value, the best variable was obtained. To increase the accuracy of estimation, designation of the extended Kalman filter was performed, which showed excellent ability to adjust the estimation period relative to the sensor property. As a result, when a three-axis gyro sensor and a three-axis acceleration sensor were adapted in the estimator, the RMS(Root Mean Square) estimation error in simulation was retained less than 1.7[$^{\circ}$], and the estimator displayed good property on the prediction of the state in 100 ms measurement period.

• Journal of Advanced Navigation Technology
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• v.20 no.5
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• pp.433-439
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• 2016

Several low-cost global navigation satellite system (GNSS) receivers do not support general range-domain correction, and DGNSS-CP (differential GNSS) method had been suggested to solve this problem. It improves its position accuracy by projecting range-domain corrections to the position-domain and then differentiating the stand-alone position by the projected correction. To project the range-domain correction, line-of-sight vectors from the receiver to each satellite should be calculated. The line-of-sight vectors can be obtained from GNSS broadcast ephemeris data or satellite direction information, and this paper shows positioning performance for the two methods. Stand-alone positioning result provided from Septentrio PolaRx4 Pro receiver was used to show the difference. The satellite direction information can reduce the computing load for the DGNSS-CP by 1/15, even though its root mean square(RMS) of position error is bigger than that of ephemeris data by 0.1m.