• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
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• pp.41-43
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• 2004

This paper is concerned with attitude estimation using low cost, small-sized accelerometers and gyroscopes. A two step extended Kalman filter is proposed, which adaptively compensates external acceleration. External acceleration is the main source of estimation error. In the proposed filter, direction of external acceleration is estimated. According to the estimated direction, the accelerometer measurement covariance matrix of the two step extended Kalman filter is adjusted. The proposed algorithm is verified through experiments.

• Communications for Statistical Applications and Methods
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• 제28권6호
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• pp.595-610
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• 2021

Recently a few articles have derived robust first-order rotatable and D-optimal designs for the lifetime response having distributions gamma, lognormal, Weibull, exponential assuming errors that are correlated with different correlation structures such as autocorrelated, intra-class, inter-class, tri-diagonal, compound symmetry. Practically, a first-order model is an adequate approximation to the true surface in a small region of the explanatory variables. A second-order model is always appropriate for an unknown region, or if there is any curvature in the system. The current article aims to extend the ideas of these articles for second-order models. Invariant (free of the above four distributions) robust (free of correlation parameter values) second-order rotatable designs have been derived for the intra-class and inter-class correlated error structures. Second-order rotatability conditions have been derived herein assuming the response follows non-normal distribution (any one of the above four distributions) and errors have a general correlated error structure. These conditions are further simplified under intra-class and inter-class correlated error structures, and second-order rotatable designs are developed under these two structures for the response having anyone of the above four distributions. It is derived herein that robust second-order rotatable designs depend on the respective error variance covariance structure but they are independent of the correlation parameter values, as well as the considered four response lifetime distributions.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.118-122
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• 2000

Nowadays, it is popular to use the spread spectrum watermarking algorithm for still image. But there is high error probability of the retrieved watermark in the spread spectrum owing to the correlation between image and spreaded watermark sequence. In this paper, two methods are proposed. One is Ordering Map Method and the other is Alteration of Image. Based on pixel value, the order by which the spreaded watermark bits is embedded is created in Ordering Map Method. By the covariance function between image and the spreaded sequence, image is altered in Alteration of Image. Hence, bit error of retrieved watermark is clearly reduced to zero by this two method.

• 대한전기학회논문지
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• 제41권9호
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• pp.1051-1059
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• 1992

In this paper, two general methods using time-series analysis in the functional separation of the myoelectric signal of human arm movements are developed. Autocorrelation, covariance method and sequential least squares algorithm were used to determine the model parameters and the order of signal model to describe six arm movement patterns` the forearm flexion and extension, the wrist pronation and supination, rotation-in and rotation-out. The confidence interval to classify the functions of arm movement was defined by the mean and standard deviation of total squared error. With the error signals of autoregressive(AR) model, the result showed that the highest success rate was obtained in the case of 4th order, and success rate was decreased with increase of order. Autocorrelation was the method of choice for better success rate. This technique might be applied to biomedical and rehabilitation engineering.

• 제어로봇시스템학회논문지
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• 제12권3호
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• pp.201-207
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• 2006

A robust Kalman filtering method for uncertain stochastic systems is suggested by adopting a perturbation estimation process which is to reconstruct total uncertainty with respect to the nominal state transition equation. The predictor and corrector of discrete Kalman filter are reformulated with the perturbation estimator. Successively, the state and perturbation estimation error dynamics and the corresponding error covariance propagation equations are derived as well. Finally we have the recursive algorithm of Combined Kalman Filter-Perturbation Estimator (CKF). The proposed combined Kalman filter-perturbation estimator has the property of integrating innovations and the adaptation capability to system uncertainties. A numerical example is shown to demonstrate the effectiveness of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.141.5-141
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• 2001

An attitude GPS receiver with 3 antennas obtains 3-dimensional attitude using GPS carrier phase measurement INS obtains the 3 dimensional navigation solution for IMU consisting of accelerometers and gyro. Ground-alignment process for the low -cost INS cannot be performed well due to the large sensor noise. Using the standard GPS receiver, however, continuous in-flight alignment for the INS becomes possible, and consequently, the errors in IMU sensors and navigation solution can be compensated. Especially with attitude measurement from the attitude GPS receiver, the compensation of errors in gyroscope and attitude would be done respite of the vehicle´s dynamics and their error covariance would be reduced. This paper presents ...

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.174-178
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• 1997

In this paper,we consider a LQG problem subject to the stochastic multirate system. By restating the problem as a periodic LQG problem, it is pointed out that the lack of measurements and control inputs in some time instants makes the problem singular. A method of transforming the problem into a nonsingular one enables us to obtain the solution,however which gives a resulting value of the LQG cost and the setimation error dynamic different with those of the original system. As a consequence, we present a optimal value of the original cost and the estimation error covariance of the original system,which are expressed by periodic Lyapunov equation respectively. The evaluation resulte can be exploited in comparing the control system performances and specifying the sampling rates.

• 대한수학회지
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• 제57권2호
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• pp.401-414
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• 2020

It is computationally expensive to compute principal components from scratch at every update or downdate when new data arrive and existing data are truncated from the data matrix frequently. To overcome this limitations, incremental principal component analysis is considered. Specifically, we present a sliding window based efficient incremental principal component computation from a covariance matrix which comprises of two procedures; simultaneous update and downdate of principal components, followed by the rank-one matrix update. Additionally we track the accurate decomposition error and the adaptive numerical rank. Experiments show that the proposed algorithm enables a faster execution speed and no-meaningful decomposition error differences compared to typical incremental principal component analysis algorithms, thereby maintaining a good approximation for the principal components.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.54-54
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• 2000

For its synergistic relationship, an integrated SDINS/GPS system has been adopted in many navigation areas. As an application of SDINS/GPS integration, the in-flight alignment process of a SDINS utilizing GPS carrier phase measurements is introduced and analyzed via an observability analysis using nul1 space method. A measurement model of double-differenced GPS carrier phase measurements is newly derived in order to be used with a SDINS error model. Also, conditions for determining the complete observability of a SDINS/GPS system are suggested and proved. Consequently, it is shown that the system is not completely observable in case of one basel me. With one baseline aligned with y-axis of body frame, pitch error and x-axis accelerometer bias are unobservable states. Also shown is that al1 states are completely observable when sequential maneuver is performed. Above results are confirmed by a covariance analysis.

• 제어로봇시스템학회논문지
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• 제1권1호
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• pp.20-24
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• 1995

In this paper we analyze the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance bounds are presented by the estimation error convariance and they are here expressed by the upper bounds of the difference of the estimation error covariance between the real and nominal values in case of the system with model uncertainties whose upper bounds are imperfrctly known a priori. The performance bounds of the optimal FIR filter are compared with those of the Kalman filter via a numerical example applied to the estimation of the motion of an aircraft carrier at sea, which shows the former has better performances than the latter.