• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.121-130
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• 2000

A practical method is proposed to improve hit probability of the digital gun fire control system, when the measured rate of the tracking sensor becomes biased under some operational situation. For ground moving target it is shown that the well-known Kalman filter which uses position measurement only can be optimally used to eliminate the rate bias error. On the other hand, for 3D moving aircraft we present a new algorithm which incorporate FIR-type filter, which uses position and rate measurement at the same time, and the fixed-lag smoother using position measurement only, and show that it has the optimal performance in terms of both estimation accuracy and response time.

• Progress in Superconductivity and Cryogenics
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• v.7 no.1
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• pp.21-24
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• 2005

The problem of fluctuation-induced digital errors in a rapid single flux quantum (RSFQ) circuit has been very important issue. So in this experiment, we calculated error rate of RSFQ switch in superconductiyity ALU, The RSFQ switch should have a very low error rate in the optimal bias. We prepared two circuits Placed in parallel. One was a 10 Josephson transmission lines (JTLs) connected in series, and the other was the same circuit but with an RSFQ switch placed in the middle of the 10 JTLs. We used a splitter to feed the same input signal to the both circuits. The outputs of the two circuits were compared with an RSFQ XOR to measure the error rate of the RSFQ switch. By using a computerized bit error rate test setup, we measured the bit error rate of 2.18$\times$$10^{12}$ when the bias to the RSFQ switch was 0.398mh that was quite off from the optimum bias of 0.6mA.

• Journal of the Korean Society of Safety
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• v.32 no.2
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• pp.7-13
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• 2017

An experimental study was conducted to identify the quantitative measurement bias for the bare-bead thermocouple (TC), which was widely used for measuring temperature in fire experiments. To this end, an apparatus could be controlled individually gas flow rate, preheating temperature and incident radiative heat flux was developed to simulate the thermal environments of fire. A relative measurement bias of bare-bead TC was evaluated with the comparison of double-shield aspirated TC. As a result, the relative measurement bias of bare-bead TC was gradually increased with the increase in radiative heat flux with constant gas temperature. The relative bias was also significantly increased with the decrease in gas temperature. Quantitatively, at the gas temperature of $20^{\circ}C$, the bare-bead TC had the relative bias of approximately 400% with the radiative heat flux of $20kW/m^2$ corresponding to thermal radiation level of the flashover. The present study was intend to provide fire researchers with methodologies for the reanalyses of temperature measured using bare-bead TC, radiation corrections, and validation of fire modeling.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.305-310
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• 2002

The measured rate of the tracking sensor becomes biased under some operational situation. For a highly maneuverable aircraft in 3D space, the target dynamics changes from time to time, and the Kalman filter using position measurement only can not be used effectively to reject the rate measurement bias error. To cope with this problem, we present a new algorithm which incorporate FIR-type filter and FIR-type fixed-lag smoother, and demonstrate that it has the optimal performance in terms of both estimation accuracy and response time through an application example to the anti-aircraft gun fire control system(AAGFCS).

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1279-1286
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• 1999

In conventional GPS/DR integration schemes, the GPS position (or pseudo-range) information is used in calibrating DR sensors. In those schemes, however, an inaccurate calibration may degrade the position accuracy when the GPS measurement is not available. This paper presents a new integration scheme where the GPS velocity information is used in calibrating DR sensors. Also proposed is a new error model of DR sensors for calibrating the bias error and the tilt error in dynamic environments. The proposed model makes it possible that the errors of both the DR sensor parameters and the velocity are calibrated using the GPS carrier-based velocity(or the pseudo-range rate) measurement while the DR position error is calibrated using the GPS position measurement. Since the DR sensors are calibrated accurately, the positioning accuracy is drastically improved when the GPS measurements are unavailable.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.33.1-33
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• 2002

The INS provides high rate position, velocity and attitude data with good short-term stability while the GPS provides position and velocity data with long-term stability. By integrating the INS with GPS, a navigation system can be achieved to provide highly accurate navigation performance. For the best performance, time synchronization of GPS and INS data is very important in GPS/INS integrated system. But, it is impossible to synchronize them exactly due to the communication and computation time-delay. In this paper, to reduce the error caused by the measurement time-delay in GPS/INS integrated systems, error compensation methods using separate bias Kalman filter are suggested for both the...

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.71-81
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• 2022

In order for electro-optical tracking system (EOTS) to have accurate target coordinate, accurate navigation results are required. If an integrated navigation system is configured using an inertial measurement unit (IMU) of EOTS and the vehicle's navigation results, navigation results with high rate can be obtained. Due to the time-delay of the navigation results of the vehicle in the EOTS and scale factor errors of the EOTS IMU in high-speed and high dynamic operation of the vehicle, it is much more difficult to have accurate navigation results. In this paper, an integrated navigation system of EOTS which compensates time-delay and scale factor error is proposed. The proposed integrated navigation system consists of vehicle's navigation system which provides time-delayed navigation results, an EOTS IMU, an inertial navigation system (INS), an augmented Kalman filter and integration Kalman filter. The augmented Kalman filter outputs navigation results, in which the time-delay of the vehicle's navigation results is compensated. The integration Kalman filter estimates position, velocity, attitude error of the EOTS INS and accelerometer bias, accelerometer scale factor error, gyro bias and gyro scale factor error from the difference between the output of the augmented Kalman filter and the navigation result of the EOTS INS. In order to check performance of the proposed integrated navigation system, simulations for output data of a measurement generator and land vehicle experiments were performed. The performance evaluation results show that the proposed integrated navigation system provides more accurate navigation results.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.1
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• pp.1-8
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• 2004

The INS(Inertial Navigation System) provides high rate position, velocity and attitude data with good short-term stability while the GPS(Global Position System) provides position and velocity data with long-term stability. By integrating the INS with GPS, a navigation system can be achieved to Provide highly accurate navigation Performance. For the best performance, time synchronization of GPS and INS data is very important in GPS/INS integrated system But, it is impossible to synchronize them exactly due to the communication and computation time-delay. In this paper, to reduce the error caused by the measurement time-delay in GPS/INS integrated systems, error compensation methods using separate bias Kalman filter are suggested for both the loosely-coupled and the tightly-coupled GPS/INS integration systems. Linearized error models for the position and velocity matching GPS/INS integrated systems are Int derived by linearizing with respect to its time-delay and augmenting the delay-state into the conventional state equations for each case. And then separate bias Kalman Inter is introduced to estimate the time-delay during only initial navigation stage. The simulation results show that the present method is effective enough resulting in considerably less position error.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.4
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• pp.531-536
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• 2014

There are trapping and stripping methods as the technique to remove the dither motion from RLG(Ring Laser Gyro) output. V/F converter output of angular sensor to measure the dither motion is used in stripping method. But bias and scale factor error is always included in V/F converter output and is a critical limiting factor for the wide application of stripping method to RLG. Therefore there have been many researches to solve this problem. The method to accurately estimate the bias and scale factor error of V/F converter using measurements of the angular sensor acquired at data sampling rate of INS is presented in this paper. To this end, stripping technique based on model of dither motion is newly applied.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.1
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• pp.21-30
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• 2022

Objectives: The purpose of this study is to suggest an optimal method by comparing the analysis methods of work environment measurement datasets including left-censored data where one or more measurements are below the limit of detection (LOD). Methods: A computer program was used to generate left-censored datasets for various combinations of censoring rate (1% to 90%) and sample size (30 to 300). For the analysis of the censored data, the simple substitution method (LOD/2), β-substitution method, maximum likelihood estimation (MLE) method, Bayesian method, and regression on order statistics (ROS)were all compared. Each method was used to estimate four parameters of the log-normal distribution: (1) geometric mean (GM), (2) geometric standard deviation (GSD), (3) 95th percentile (X95), and (4) arithmetic mean (AM) for the censored dataset. The performance of each method was evaluated using relative bias and relative root mean squared error (rMSE). Results: In the case of the largest sample size (n=300), when the censoring rate was less than 40%, the relative bias and rMSE were small for all five methods. When the censoring rate was large (70%, 90%), the simple substitution method was inappropriate because the relative bias was the largest, regardless of the sample size. When the sample size was small and the censoring rate was large, the Bayesian method, the β-substitution method, and the MLE method showed the smallest relative bias. Conclusions: The accuracy and precision of all methods tended to increase as the sample size was larger and the censoring rate was smaller. The simple substitution method was inappropriate when the censoring rate was high, and the β-substitution method, MLE method, and Bayesian method can be widely applied.