• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.689-694
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• 2008

This paper proposes a roll rate estimation method for spinning vehicles. The carrier phase and frequency variations caused by spinning of vehicles are observed and the roll rate estimator is designed on the observation. The roll rate estimator consists of phase detector and zero crossing counter. The phase detector computes phase variation using in-phase and quadrature value from the correlator. By using zero crossing counter, the roll rate can be estimated since the output of phase detector is changed in proportion to the roll rate. Experiment a results show that estimated roll rate error is smaller than 0.0578Hz.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.797-802
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• 2013

In this paper, using the mass/CG measurement equipment and the MOI measurement equipment developed in-house, Pitch MOI and Roll MOI of test specimen were measured and measurement uncertainties on MOI were studied. The possible factors of the measurement uncertainty that could affect accuracy of MOI measurement were mass, spring, frequency, and length measurement-related elements. The each combined standard uncertainty of pitch MOI and roll MOI was estimated from the uncertainties of the above various factors.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.208-214
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• 2014

Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.177-186
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• 2017

Recently, Autonomous vehicles are getting hot attention. Amazon, the biggest online shopping service provider is developing a delivery system that uses drones. This kinds of platforms are need accurate attitude information for navigation. In this paper, a structure design of AHRS using low-cost inertia sensor is proposed. To estimate attitudes a Kalman filter which uses a quaternion based dynamic model, bias-removed measurements from MEMS Gyro, raw measurements from MEMS accelerometer and magnetometer, is designed. To remove bias from MEMS Gyro, an additional Kalman filter which uses raw Gyro measurements and attitude estimates, is designed. The performance of implemented AHRS is compared with high price off-the-shelf 3DM-GX3-25 AHRS from Microstrain. The Gyro bias was estimated within 0.0001[deg/s]. And from the estimated attitude, roll and pitch angle error is smaller than 0.2 and 0.3 degree. Yaw angle error is smaller than 6 degree.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.11
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• pp.965-972
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• 2016

This paper presents results of flight experiments on a navigation algorithm including multiplicative extended Kalman filter for estimating attitude of the guided munition. The filter describes orientation of aircraft by data fusion with low-cost sensors where measurement update is done by multiplication, rather than addition, which is suitable for quaternion representation. In determining attitude from vector observations, the existing approach utilizes a 3-axis accelerometer as a 2-axis inclinometer by measuring gravity to estimate pitch and roll angles, while GNSS velocity is used to derive heading of the vehicle. However, during accelerated maneuvers such as coordinated flight, the accelerometer provides inadequate inclinometer measurements. In this paper, the measurement update process is newly defined to complement the vulnerability by using different vector observations. The acceleration measurement is considered as a result of a centrifugal force and gravity during turning maneuvers and used to estimate roll angle. The effectiveness of the proposed method is verified through flight experiments.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.5
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• pp.615-621
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• 2009

Since GPS receivers and INS algorithms do not work properly in the spinning vehicles due to change of the GPS signal and excess of the measurement limitation of the gyroscope, conventional GPS/INS integrated navigation systems do not provide accurate navigation outputs. This paper proposes a design method for GPS/INS integrated navigation systems of spinning vehicles. A special GPS receiver with a signal tracking loop for changed GPS signal caused by spinning and an INS with a roll estimation method are configured and the conventional integration filter is combined. The proposed method was verified through comparison of the navigation results. The result of the proposed method for the spinning vehicle was similar to that of the conventional navigation system without spinning.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.631-640
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• 2017

The estimation of rice yield affects the income of farmers as well as the fields related to agriculture. Moreover, it has an important effect on the government's policy making including the control of supply demand and the price estimation. Thus, it is necessary to build the crop yield estimation model and from the past, many studies utilizing empirical statistical models or artificial neural network algorithms have been conducted through climatic and satellite data. Presently, scientists have achieved successful results with deep learning algorithms in the field of pattern recognition, computer vision, speech recognition, etc. Among deep learning algorithms, the SSAE (Stacked Sparse AutoEncoder) algorithm has been confirmed to be applicable in the field of forecasting through time series data and in this study, SSAE was utilized to estimate the rice yield in South Korea. The climatic and satellite data were used as the input variables and different types of input data were constructed according to the period of rice growth in South Korea. As a result, the combination of the satellite data from May to September and the climatic data using the 16 day average value showed the best performance with showing average annual %RMSE (percent Root Mean Square Error) and region %RMSE of 7.43% and 7.16% that the applicability of the SSAE algorithm could be proved in the field of rice yield estimation.

• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.165-187
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• 2005

This paper tries to investigate the relationships among stock return volatility, time-varying risk premium and Korea Discount. Using Korean Composite Stock Price Index (KOSPI) return from January 4, 1980 to August 31, 2005, this study finds possible links between time-varying risk premium and Korea Discount. First of all, this study classifies Korean stock returns during the sample period by three regime-switching volatility period that is to say, low-volatile period medium-volatile period and highly-volatile period by estimating Markov-Switching ARCH model. During the highly volatile period of Korean stock return (09/01/1997-05/31/2001), the estimated time-varying unit risk premium from the jump-diffusion GARCH model was 0.3625, where as during the low volatile period (01/04/1980-l1/30/1985), the time-varying unit risk premium was estimated 0.0284 from the jump diffusion GARCH model, which was about thirteen times less than that. This study seems to find the evidence that highly volatile Korean stock market may induce large time-varying risk premium from the investors and this may lead to Korea discount.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.10
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• pp.79-88
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• 2003

The paper presented here covers the work associated with the flight control law design, ground based and in flight simulation and handling qualities assessment of the Fly-by-Wire type Aircraft (FBWA). The FBWA configurations are of the same generic form of the Korean advanced trainer. The normal acceleration (Nz) and pitch rate (q) feedback control system is employed for longitudinal axis and roll rate (p) and lateral acceleration (Ny) feedback flight control law is developed in lateral/ directional axis. The flight tests for the FBW A dynamics evaluation were executed for the target aircraft (FBWA) on the IFS (In-Flight-Simulator) aircraft . The test results showed that Level 1 handling qualities for the most unstable flight regime and Level 1/2 for the landing approach flight regime were achieved. And the designed FBWA flight control law has revealed acceptable CHR (Cooper-Harper handling qualities Ratings).

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.731-740
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• 1999

Autocorrelation function is widely used as a tool measuring linear dependence of hydrologic time series. However, it may not be appropriate for choosing decorrelation time or delay time ${\tau}_d$ which is essential in nonlinear dynamics domain and the mutual information have recommended for measuring nonlinear dependence of time series. Furthermore, some researchers have suggested that one should not choose a fixed delay time ${\tau}_d$ but, rather, one should choose an appropriate value for the delay time window ${\tau}_d={\tau}(m-1)$, which is the total time spanned by the components of each embedded point for the analysis of chaotic dynamics. Unfortunately, the delay time window cannot be estimated using the autocorrelation function or the mutual information. Basically, the delay time window is the optimal time for independence of time series and the delay time is the first locally optimal time. In this study, we estimate general dependence of hydrologic time series using the C-C method which can estimate both the delay time and the delay time window and the results may give us whether hydrologic time series depends on its linear or nonlinear characteristics which are very important for modeling and forecasting of underlying system.