• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.45-53
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• 2004

In this paper, an INS compensation algorithm for auto sailing system is proposed, where low cost IMU (Inertial Measurement Unit) is used for measuring the accelerometer data. First, we denote the basic INS algorithm with IMU and show that how to compensate the error of position by using low cost IMU. Second, in considering the ship's characteristic and ocean environments, we consider with a factor as a periodic external disturbance which effects to the exact position. To develop the compensation algorithm, we use a repetitive method to reduce the external environment changes. Lastly, we verify the proposed algorithm by using experiments results.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2003.10a
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• pp.113-116
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• 2003

Confluence buffers and single flux quantum (SFQ) switches are essential components in constructing a high speed superconductive Arithmetic Logic Unit (ALU). In this work, we developed a SFQ confluence buffer and an SFQ switch. It is very important to optimize the circuit parameters of a confluence buffer and an SFQ switch to implement them into an ALU. The confluence buffer that we are currently using has a small bias margin of $\pm$11％. By optimizing it with a Josephson circuit simulator, we improved the design of confluence buffer. Our simulation study showed that we improved bias global margin of 10％ more than the existent confluence buffer. In simulations, the minimal bias margin was $\pm$33％. We also designed, fabricated, and tested an SFQ switch operating in a DC mode. The mask layout used to fabricate the SFQ switch was obtained after circuit optimization. The test results of our SFQ switch showed that it operated correctly and had a reasonably wide margin of $\pm$15％.

• Atmosphere
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• v.23 no.4
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• pp.453-470
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• 2013

As a part of the KIAPS Observation Processing System (KOPS), we have developed the modules of satellite radiance data pre-processing and quality control, which include observation operators to interpolate model state variables into radiances in observation space. AMSU-A (Advanced Microwave Sounding Unit-A) level-1d radiance data have been extracted using the BUFR (Binary Universal Form for the Representation of meteorological data) decoder and a first guess has been calculated with RTTOV (Radiative Transfer for TIROS Operational Vertical Sounder) version 10.2. For initial quality checks, the pixels contaminated by large amounts of cloud liquid water, heavy precipitation, and sea ice have been removed. Channels for assimilation, rejection, or monitoring have been respectively selected for different surface types since the errors from the skin temperature are caused by inaccurate surface emissivity. Correcting the bias caused by errors in the instruments and radiative transfer model is crucial in radiance data pre-processing. We have developed bias correction modules in two steps based on 30-day innovation statistics (observed radiance minus background; O-B). The scan bias correction has been calculated individually for each channel, satellite, and scan position. Then a multiple linear regression of the scan-bias-corrected innovations with several predictors has been employed to correct the airmass bias.

• Survey Research
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• v.10 no.1
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• pp.169-186
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• 2009

The propensity score method is used to minimize the bias level in social survey, which comes from nonresponse. The theoretical concept and the background of the propensity score method is discussed first. The propensity score method was first applied in the epidemiology observational study. I have summarized the process of the three propensity score methods that were used to reduce estimation bias in this study. Matching by propensity score is applied to the relatively large control group. Subclassification has the advantage of using whole control group data and regression adjustment is applied to multiple covariates as well as propensity score of each unit is computable and usable. Lastly, the application procedures of propensity score method to reduce the nonresponse bias is suggested and its applicability to real situation is reviewed with the existing data.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.299-303
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• 2018

Generally, when predicting the accuracy of the anti-air artillery system, the error is classified as fixed bias, variable bias, and random error. Then the standard deviation on the target is expressed as the square root of the squared sum of each error value which comes from the random error and variable bias and in the case of fixed bias, the mean value is shifted as the sum of errors from the fixed bias. At this time, the variables indicating the displacement of the direction of azimuth and elevation direction with regard to the change of the unit value of each error are weighted. These errors are then used to predict the system's delivery accuracy through a normally distributed integral. This paper presents a method of predicting system accuracy by considering the correlation of errors. This approach shows that it helps to predict the delivery accuracy of the system, precisely.

• Atmosphere
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• v.24 no.4
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• pp.491-502
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• 2014

As a part of the KIAPS (Korea Institute of Atmospheric Prediction Systems) Package for Observation Processing (KPOP), we have developed the modules for Advanced Microwave Sounding Unit-A (AMSU-A) pre-processing and its bias correction. The KPOP system calculates the airmass bias correction coefficients via the method of multiple linear regression in which the scan-corrected innovation and the thicknesses of 850~300, 200~50, 50~5, and 10~1 hPa are respectively used for dependent and independent variables. Among the four airmass predictors, the multicollinearity has been shown by the Variance Inflation Factor (VIF) that quantifies the severity of multicollinearity in a least square regression. To resolve the multicollinearity, we adopted simple linear regression and Principal Component Regression (PCR) to calculate the airmass bias correction coefficients and compared the results with those from the multiple linear regression. The analysis shows that the order of performances is multiple linear, principal component, and simple linear regressions. For bias correction for the AMSU-A channel 4 which is the most sensitive to the lower troposphere, the multiple linear regression with all four airmass predictors is superior to the simple linear regression with one airmass predictor of 850~300 hPa. The results of PCR with 95% accumulated variances accounted for eigenvalues showed the similar results of the multiple linear regression.

• Journal of Ocean Engineering and Technology
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• v.17 no.6
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• pp.83-90
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• 2003

This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), and a Doppler velocity log (DVL), accompanied by a magnetic compass. The errors of inertial measurement units increase with time, due to the bias errors of gyros and accelerometers. A navigational system model is derived, to include the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 20. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors, and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o,f equations of motion of SAUV, using a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance, by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass, and a depth sensor. The error of the estimated position still slowly drifts in the horizontal plane, about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.61-73
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• 2004

Rotation sampling designs may be classified into two categories. The first type uses the same sample unit for the entire life of the survey. The second type uses the sample unit only for a fixed number of times. In both type of designs, the entire sample is partitioned into a finite number(=G) of rotation groups. This paper is generalization of the first type designs. Since the generalized design can be identified by only G rotation groups and recall level 1, we denote this rotation system as l/G rotation design. Under l/G rotation design, variance and mean squared error (MSE) of generalized composite estimator are derived, incorporating two type of biases and exponentially decaying correlation pattern. Compromising MSE's of some selected l/G designs, we investigate design efficiency, design gap effect, ans the effects of correlation and bias.

• Journal of Ocean Engineering and Technology
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• v.18 no.4 s.59
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• pp.33-39
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• 2004

This paper presents a hybrid underwater navigation system for unmanned underwater vehicles, using an additional range sonar, where the navigation system is based on inertial and Doppler velocity sensors. Conventional underwater navigation systems are generally based on an inertial measurement unit (IMU) and a Doppler velocity log (DVL), accompanying a magnetic compass and a depth sensor. Although the conventional navigation systems update the bias errors of inertial sensors and the scale effects of DVL, the estimated position slowly drifts as time passes. This paper proposes a measurement model that uses the range sonar to improve the performance of the IMU-DVL navigation system, for extended operation of underwater vehicles. The proposed navigation model includes the bias errors of IMU, the scale effects of VL, and the bias error of the range sonar. An extended Kalman filter was adopted to propagate the error covariance, to update the measurement errors, and to correct the state equation, when the external measurements are available. To illustrate the effectiveness of the hybrid navigation system, simulations were conducted with the 6-d.o.f. equations of motion of an AUV in lawn-mowing survey mode.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.361-365
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• 2002

Rain-rate retrieval using the NOAA/AMSU (Advanced Microwave Sounding Unit) (Zaho et al., 2001) has been implemented at METRI/KMA since 2001. Here, we present the results of the AMSU derived rain-rate and validation result, especially for the rainfall associated with the tropical cyclone for 2001. For the validation, we use rain-rate derived from the ground based radar and/or rainfall observation from the rain gauge in Korea. We estimate the bias score, threat score, bias, RMSE and correlation coefficient for total of 16 tropical cyclone cases. Bias score shows around 1.3 and it increases with the increasing threshold value of rain-rate, while the threat score extends from 0.4 to 0.6 with the increasing threshold value of precipitation. The averaged rain-rate for at all 16 cases is 3.96mm/hr and 1.41mm/hr for the retrieved from AMSU and the ground observation, respectively. On the other hand, AMSU rain-rate shows a much better agreement with the ground based observation over inner part of tropical cyclone than over the outer part (Correlation coefficient for convective region is about 0.7, while it is only about 0.3 over the stratiform region). The larger discrepancy of tile correlation coefficient with the different part of the tropical cyclone is partly due to the time difference in between ice water path and surface rainfall. This results indicates that it might be better to develop the algorithm for different rain classes such as convective and stratiform.