• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.664-667
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• 1996

This paper presents the error parameter estimation technique for IMU(Inertial Measurement Unit) which is core sensor of INS(Inertial Navigation System) and verifies it via laboratory test. Firstly the error characteristic of gyroscope and accelerometer which is contained in IMU is examined and the error modelling is executed. The error of IMU can be divided into deterministic and random part, and the deterministic error can be divided into static and dynamic part. This paper consider the random part as constant. Secondly the error parameter estimation technique and following procedure for laboratory test is explained. Thirdly according to the test procedure the IMU test for static error is executed using 2-axis rate table and estimation result is presented with discussion about its validity.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.10 no.1
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• pp.27-32
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• 2011

These days more electric devices are implemented in car, and more accurate estimation of SoC is required. OCV with current integration and Internal Resistance is essential method of Battery SoC Estimation. In this paper we propose OCV with current integration method and compare with Internal Resistance method. In OCV with current integration method estimation error was less than average 2%, but requires more than 5 minutes to stabilize OCV. If Stop and Running conditions are change frequently, estimation error will increase. In Internal resistance Modeling method, in high SoC state, estimation error was more than 15%, and in low SoC state, estimation error was less than 8%.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.428-433
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• 1999

The errors of IMU(Inertial Measurement Unit) can be divided into deterministic and random errors. Since the required accuracy of the IMU is very high, the errors must be compensated by using an accurate error mode. In this paper, we present a method to get a more accurate error model in a laboratory test. This was done by considering the setting misalignment in the laboratory test in the IMU error model. We considered here the IMU which consits of DTG(dynamically tuned gyroscope) and pendulum type accelerometer. First, it was shown that the estimation result from the model which does not contain the setting misalignment gives considerable estimation error at the validation test. Second, a new model considering the setting misalignment was derived. Finally, by validation test using the estimation results from new model the validity of it was proved.

• Journal of Communications and Networks
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• v.16 no.3
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• pp.301-304
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• 2014

This paper proposes accurate interference probability and bit error rate formulas for cognitive relay networks with underlay spectrum sharing and channel estimation error (CEE). Numerous results reveal that the CEE not only degrades the performance of secondary systems (SSs) but also increases interference power caused by SSs to primary systems (PSs), eventually unfavorable to both systems. A solution to further protect PSs from this effect through reducing the power of secondary transmitters is investigated and analyzed.

• Kyungpook Mathematical Journal
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• v.58 no.3
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• pp.453-462
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• 2018

In this paper, we present a symbolic formulation of the error obtained due to an approximation of a given function by the mixed-interpolating function. Using the proposed symbolic method, we compute the error evaluation operator as well as the error estimation at any arbitrary point. We also present an algorithm to compute an approximation of a function by the mixed interpolation technique in terms of projector operator. Certain examples are presented to illustrate the proposed algorithm. Maple implementation of the proposed algorithm is discussed with sample computations.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.64-69
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• 1993

In this paper we present the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance measure bounds are calculated from the estimation error covariance bounds of the optimal FIR filter and the suboptimal FIR filter. Performance error bounds range are expressed by the upper bounds on the estimation error covariance difference between the real and nominal values in case of the systems with noise uncertainty or model uncertainty. The performance bounds of the systems are derived on the assumption that the system uncertainty and the estimation error covariance are imperfectly known a priori. The estimation error bounds of the optimal FIR filter is 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.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.352-355
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• 1995

In this paper, estimation error bounds of the optimal FIR (Finite Impulse Response) filter, which is proposed by Kwon et al.[1, 2], are presented in discrete-time systems with the model uncertainty. Performance bounds are here represented by the upper bounds on the difference of the estimation error covariances between the nominal and real values in case of the systems with the noise or model parameter uncertainty. The estimation error bounds of the discrete-time optimal FIR filter is compared with those of the Kalman filter via a numerical example applied to the simulation problem by Toda and Patel[3]. Simulation results show that the former has robuster performance than the latter.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.466-472
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• 2007

Single carrier block transmission with frequency domain equalization(SC-FDE) has been shown to be a promising candidate in ultra-wideband(UWB) communications. In this paper, we analyze the performance of SC-FDE over UWB communications with channel estimation error. The probability density functions of the frequency domain minimum mean-squared error(MMSE) equalizer taps are derived in closed form. The error probabilities of single carrier block transmission with frequency domain MMSE equalization under imperfect channel estimation are presented and evaluated numerically. Compared with the simulation results, our semi-analytical analysis yields fairly accurate bit error rate performance, thus validating the use of the Gaussian approximation method in the performance analysis of the SC-FDE system with channel estimation error.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.155-162
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• 2011

It is using to incident angle estimation technique in order to target estimation in radar. This paper was estimated incident angle estimation for target using adaptive array incident angle and single look error incident angle estimation technique. We estimated signal incident angle of target to removal main lobe and side lobe to adaptive array incident angle technique. It is difficult to correctly target estimation because single look technique increase direction error of signal incident angle. In order to receive a desired target signal must be not almost look error between signal incident angle and look angle. we had decreased to occur a look error using delay time and single look condition to calculation a covariance when incident angle estimate. Through simulation, we show that the proposed incident angle estimation technique improves the performance of target estimation compared to previous method.

• Journal of Satellite, Information and Communications
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• v.12 no.2
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• pp.104-111
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• 2017

Pre-Rake CDMA system using multiple transmit antenna provides a good system performance without equipping a complicated RAKE combiner at the mobile receiver. However, the performance of the Pre-Rake systems are significantly affected by channel estimation error so that the effect of the channel estimation error should be considered and analyzed for evaluating the system performance. In this paper, MISO(Multi-Input Multi-output) Pre-Rake CDMA system with channel estimation error is analyzed by numerical analysis and the results are compared with that of the computer simulation. From the numerical results, it is found that the performance of the Pre-Rake system is more affected by the phase error than the amplitude error.