• Journal of Astronomy and Space Sciences
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• v.34 no.1
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• pp.19-30
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• 2017

The optical wide-field patrol network (OWL-Net) is a Korean optical surveillance system that tracks and monitors domestic satellites. In this study, a batch least squares algorithm was developed for optical measurements and verified by Monte Carlo simulation and covariance analysis. Potential error sources of OWL-Net, such as noise, bias, and clock errors, were analyzed. There is a linear relation between the estimation accuracy and the noise level, and the accuracy significantly depends on the declination bias. In addition, the time-tagging error significantly degrades the observation accuracy, while the time-synchronization offset corresponds to the orbital motion. The Cartesian state vector and measurement bias were determined using the OWL-Net tracking data of the KOMPSAT-1 and Cryosat-2 satellites. The comparison with known orbital information based on two-line elements (TLE) and the consolidated prediction format (CPF) shows that the orbit determination accuracy is similar to that of TLE. Furthermore, the precision and accuracy of OWL-Net observation data were determined to be tens of arcsec and sub-degree level, respectively.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.9
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• pp.88-93
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• 2004

A method is suggested for validating the existence of bias error on GPS carrier measurement. The baseline constraint is used as an addition measurement, which augments the original measurement equation. The detection probability is calculated on both cases. The first case is using GPS carrier measurement only, the second case is using GPS carrier and a baseline constraint. The improvement of the detection probability is shown, and the advantage of using baseline constraint is described statistically, the results of the simulation is shown and analyzed.

• Journal of the Korean earth science society
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• v.41 no.4
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• pp.356-366
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• 2020

The accuracy of satellite-observed sea surface salinity (SSS) was evaluated in comparison with in-situ salinity measurements from ARGO floats and buoys in the seas around the Korean Peninsula, the northwest Pacific, and the global ocean. Differences in satellite SSS and in-situ measurements (SSS errors) indicated characteristic dependences on geolocation, sea surface temperature (SST), and other oceanic and atmospheric conditions. Overall, the root-mean-square (rms) errors of non-averaged SMOS SSSs ranged from approximately 0.8-1.08 psu for each in-situ salinity dataset consisting of ARGO measurements and non-ARGO data from CTD and buoy measurements in both local seas and the ocean. All SMOS SSSs exhibited characteristic negative bias errors at a range of -0.50- -0.10 psu in the global ocean and the northwest Pacific, respectively. Both rms and bias errors increased to 1.07 psu and -0.17 psu, respectively, in the East Sea. An analysis of the SSS errors indicated dependence on the latitude, SST, and wind speed. The differences of SMOS-derived SSSs from in-situ salinity data tended to be amplified at high latitudes (40-60°N) and high sea water salinity. Wind speeds contributed to the underestimation of SMOS salinity with negative bias compared with in-situ salinity measurements. Continuous and extensive validation of satellite-observed salinity in the local seas around Korea should be further investigated for proper use.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.293-301
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• 2011

The ionospheric delay is the largest error source in GPS positioning after the SA effect has been turned off in May, 2000. In this study, we used 44 permanent GPS stations being operated by National Geographic Information Institute (NGII) to estimate Total Electron Content (TEC) based on pseudorange measurements phase-leveled by a linear combination with carrier phases. The Differential Code Bias (DCB) of GPS satellites and receivers was estimated and applied for an accurate estimation of the TEC. To validate our estimates of DCB, changes of TEC values after DCB application were investigated. As a result, the RMS error went down by about an order of magnitude; from 35~45 to 3~4 TECU. After the DCB correction, ionospheric TEC maps were produced at a spatial resolution of $1^{\circ}{\times}1^{\circ}$. To analyze the effect of the number of sites used for map generation on the accuracy of TEC values, we tried 10, 20, 30, and 44 stations and the RMS error was computed with the Global Ionosphere Map as the truth. While the RMS error was 5.3 TECU when 10 sites are used, the error reduced to 3.9 TECU for the case of 44 stations.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.527-538
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• 2019

This paper considers the issue of obtaining the optimal design in Poisson regression model when the sample size is small. Poisson regression model is widely used for the analysis of count data. Asymptotic theory provides the basis for making inference on the parameters in this model. However, for small size experiments, asymptotic approximations, such as unbiasedness, may not be valid. Therefore, first, we employ the second order expansion of the bias of the maximum likelihood estimator (MLE) and derive the mean square error (MSE) of MLE to measure the quality of an estimator. We then define DM-optimality criterion, which is based on a function of the MSE. This criterion is applied to obtain locally optimal designs for small size experiments. The effect of sample size on the obtained designs are shown. We also obtain locally DM-optimal designs for some special cases of the model.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.255-264
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• 2015

This paper addressed the problem of estimation of finite population mean in double sampling for stratification. This paper proposed a generalized ratio-cum-product type estimator of population mean. The bias and mean square error of the proposed estimator has been obtained upto the first degree of approximation. A particular member of the proposed generalized estimator was identified and studied from a comparison point of view. It is observed that the identified particular estimator is more efficient than usual unbiased estimator and Ige and Tripathi (1987) estimators. An empirical study was conducted in support of the theoretical findings.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1137-1142
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• 2010

This paper studied the speech parameters less affected by the human emotion for the development of the robust speech recognition system. For this purpose, the effect of emotion on the speech recognition system and robust speech parameters of speech recognition system were studied using speech database containing various emotions. In this study, mel-cepstral coefficient, delta-cepstral coefficient, RASTA mel-cepstral coefficient and frequency warped mel-cepstral coefficient were used as feature parameters. And CMS (Cepstral Mean Subtraction) method were used as a signal bias removal technique. Experimental results showed that the HMM based speaker independent word recognizer using vocal tract length normalized mel-cepstral coefficient, its derivatives and CMS as a signal bias removal showed the best performance of 0.78% word error rate. This corresponds to about a 50% word error reduction as compare to the performance of baseline system using mel-cepstral coefficient, its derivatives and CMS.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.8
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• pp.1260-1264
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• 1990

A voltage controlled CMOS operational transconductance amplifier (OTA), whose transconductance is directly proportional to the DC bias voltage, has been designed for many electronic circuit applications. It consists of a differential pair and three ourrent mirrors. The SPICE simulation shows that the conversion sensitivity of the OTA is 41.817 \ulcornerho/V and the linearity error is less than 0.402% over a bias voltage range from -2. OV to 1. OV. Electrically tunalble filters based on voltage controlled impedances, which are realized with OTA's, also have been designed. The SPICE simulation shows that a second-order bandpass filter, whose center frequency is 23KHz at -1. OV, has the conversion sensitivity 6.6KHz/V and the linearity error less than 0.822% over a voltage range from -2.OV tp 1.OV, Tne OTA has been laid out with the 3\ulcorner n-well CMOS design rule adopted in ISRC (inter-university semiconductor research center). The chip size was about $0.756x0.945mm^2$.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.130.4-130
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• 2001

In this paper, a measurement system of moving distance is developed. The error compensation method is also proposed using the characteristics of walking motion. As personal navigation systems and multimedia systems are emerging into the commericial market, men´s moving distance is considered as one of the important information. GPS offers the information easily but GPS can be used only when the satellites are visible. INS can calculate the moving distance anywhere but error is increased with time due to the sensor bias. In this paper, to detect the human walking distance a measurement system of moving distance only using low-cost accelerometer is developed. The sensor bias is estimated and compensated using the walking motion characteristics. The performanced of the proposed system is verified by experiment.

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.4
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• pp.365-368
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• 1995

Lactation curves of dairy cows were generated using three models, namely; incomplete gamma function (model 1), polynomial inverse function (model 2) and non-linear regression (model 3). Secondary milk yield data of 27 cows which had completed 6 lactations were used in this study. Milk yield records (once a week) throughout the lactation and from the first three months of lactation were fitted to the models. Estimation of total milk yield by model 3 using the data once a week throughout the lactation resulted in smaller % bias and standard error than those generated from model 1 and 2. But, model 2 was more accurate in predicting the 305-day milk yield equivalent closer to actual yields with smaller bias % and error using partial records up to 3 months. Also, model 2 was able to estimate the time to reach peak yield close to the actual data using partial records and model 2 could be used as a tool to advise farmers on appropriate feeding and management practices to be adopted.