• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.2
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• pp.189-196
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• 2019

The inertial sensor errors in SDINS(Strapdown Inertial Navigation System) can be compensated by rotating the inertial measurement unit and it is called RINS(Rotational Inertial Navigation System). It is assumed that the error of the inertial sensor in RINS is a static bias. However, the error of the inertial sensor actually developed and produced is not a static bias due to the change of the temperature applied to the sensor and the influence of the earth's gravity acceleration. In this paper, we propose a six-position gyro bias calibration method to evaluate the gyro bias required for RINS and present the test results of applying it to a ring laser gyro inertial navigation system under development.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.874-881
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• 2001

By showing the existence of the ARE solution and the convergence property of the DRE solution, this paper proves that a Kalman filter for the linear system with the unobservable bias is stable. It is also shown that the Kalman filter has a biased steady state estimation error whose covariance is affected mainly by the unobservable bias. Finally, the results are illustrated through a 2nd order system example including the inertial navigation system.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.401-406
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• 1992

When a velocity-aided strapdown inertial navigation system is loaded into a torpedo subjected to an extraneous force by the current, odometer measurement errors occur seriously. In order to compensate for navigation errors induced by large odometer biases, the Kalman Filter with separate bias estimator is applied, which separately estimates an unknown bias, and corrects the state estimate produced by the bias-free Kalman Filter to reflect the effect of the bias estimate.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1243-1251
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• 2007

In this paper a study on the simplified observability analysis of GPS/INS is introduced. Errors for the position, velocity, attitude, gyro and accelerometer biases, and lever arm between GPS antenna and inertial sensors are considered in the observablity analysis. From the error dynamics model in which relatively small terms are neglected, simple observability conditions are obtained such that the observability of GPS/INS is determined by the test on the attutude, gyro bias, and lever arm. Unobservable errors for the position, velocity, and accelerometer bias are determined by those for the attitude, gyro bias, and lever arm. The simplified observability conditions are applied to a constant speed horizontal motion. It is shown that there are seven unobservable modes for the motion including the vertical component of gyro bias. The analytic observability analysis results are confirmed with a covariance simulation.

• Journal of IKEEE
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• v.23 no.1
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• pp.120-126
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• 2019

Recently, accurate prediction of power consumption based on machine learning techniques in Internet of Energy (IoE) has been actively studied using the large amount of electricity data acquired from advanced metering infrastructure (AMI). In this paper, we propose a deep learning model based on Gated Recurrent Unit (GRU) as an artificial intelligence (AI) network that can effectively perform pattern recognition of time series data such as the power consumption, and analyze performance of the prediction based on real household power usage data. In the performance analysis, performance comparison between the proposed GRU-based learning model and the conventional learning model of Long Short Term Memory (LSTM) is described. In the simulation results, mean squared error (MSE), mean absolute error (MAE), forecast skill score, normalized root mean square error (RMSE), and normalized mean bias error (NMBE) are used as performance evaluation indexes, and we confirm that the performance of the prediction of the proposed GRU-based learning model is greatly improved.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1227-1234
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• 2015

Traditional criteria for optimum experimental designs depend on the specifications of the model; however, there will be a dilemma when we do not have perfect knowledge about the model. Box and Draper (1959) suggested one direction to minimize bias that may occur in this situation. We will demonstrate some examples with exact solutions that provide a no-bias design for polynomial regression. The most interesting finding is that a design that requires less bias should allocate design points away from the border of the design space.

• 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.

• The Research Journal of the Costume Culture
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• v.12 no.1
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• pp.28-40
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• 2004

The purpose of this study was (1) to identify the experimental bias which could appear person perception as results of development methods (2) to find out the most desirable method in developments of stimulus. The research was a quasi experiment and the subjects were 358 male and female undergraduate students by convenient sampling. The experimental instruments consisted of a set of stimulus and semantic differential scales of 7-point bi-polar adjectives. The collected data were analyzed by Principle Component Analysis, ANOVA(analysis of variance), Scheffe's multiple range test. The independent variables were developing methods of stimulus(live person, photography of real person, 2 kinds of black and white line drawing, 2 kinds of color drawing). The results were as follows. First, five factors which were potency, sociality, appearance, evaluation, activity impressional dimensions emerged to account for the methods of development of stimulus. Second, the methods of development of stimulus had significant effects on potency, sociality, appearance, activity factors. In sociality factors, the impression of photographic stimulus was the closest to the live person's impression. However in the appearance and activity impressions, significant difference existed between live person and other developing stimulus. In the potency impression, black and white line-drawing gave the highest impressional bias. In the sociability and appearance impressions, color-drawing stimulus gave the highest impressional bias. Result: On conclusion the developments of stimulus can effect on stimulus person's impressions and these effects can produce experimental biases, the photographic stimulus gave the least impressional bias. The study shows that photography of real person will produce minimize measurement error.

• Bulletin of the Korean Space Science Society
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• 2010.04a
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• pp.27.5-28
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• 2010

The unexpected observation condition or insufficient measurement modeling can lead to uncertain measurement errors. The uncertain measurement error of orbit determination problem typically consists of noise, bias and drift. It must be removed by using a proper estimation process for better orbit accuracy. The estimation of noise and drift is not easy because of their random or unpredictable variation. On the other hand, bias is a constant difference between the mean of the measured values and the true value, so it can be simply removed. In this study, precision orbit determination with SLR observations considering range bias estimation is presented. The Yonsei Laser-ranging Precision Orbit Determination System (YLPODS) and SLR NP (Normal Point) observations of CHAMP satellite are used for this work. The SLR residual test is performed to estimate the range bias of each arc. The result shows that we can get better orbit accuracy through range bias estimation.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.261-264
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• 2005

This paper presents the design of a down-conversion mixer with built-in active balun integrated in a $0.25\;{\mu}m$ pHEMT process. The active balun consists of series-connected common-gate FET and common-source FET. The designed balun achieved broadband characteristics by optimizing gate-width and bias condition for the reduction in parasitic effect. From DC to more than 6GHz, the active balun shows the phase error of less than 3 degree and the gain error of less than 0.4 dB. A single-balanced down-conversion mixer with built-in broadband active balun has been designed with optimum width, load resistor and bias for conversion gain and without any matching component for broadband operating. The designed mixer whose size of including on-chip bias circuit is $1\;mm{\times}1\;mm$ shows the conversion gain of better than 7 dB from 2 GHz to 6 GHz and $P_{1dB}$ of -10 dBm at 5.8 GHz