• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.150-154
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• 2022

The Automatic Ship Identification System(AIS) is importantly used to evaluate the trajectory of ships and the possibility of collision between ships. However, it is difficult to provide real-time information due to the limitation of the transmission intervals. Most of the studies to improve this are conducted based on ideal data, so there is a problem that it is hard to respond to the actual situation. Therefore, in this paper, we propose a discrete Kalman filter-based method that reflects the turning angle according to the type of trajectory, to provide real-time position information on real-time data. In addition, the accuracy evaluation of the proposed algorithm is conducted through experiments using actual data.

• Journal of the Korean Society for Railway
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• v.11 no.2
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• pp.203-210
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• 2008

Since hub wheel BLDC Motor consisted of wheel and BLDCM (Brushless DC Motor) without gear reducer has high efficiency and low operation noise, it can be utilized to a driving wheel at some light rail systems. However, installing sensors for speedometer on a Hub-Wheel motor is not easy, so it requires a different speed control mechanism method for speed measurement. This paper introduces a speed control method based on simple mathematical model which uses discrete Kalman Filter to estimate and control the speed of the motor.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.470-473
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• 1989

본 논문은 상태 변수 모델 하에서 유도된 최적 FIR 필터의 해를 이용한 새로운 이산 퓨리에 변환 방법을 제시한다. 이 방법은 측정 잡음 하에서 시변 하모닉스 성분을 추정하는데 특히 유용하여, 기존의 이산 퓨리에 변환 보다 훨씬 효과적인 노이즈 억제성능을 얻을 수 있으며 또한 칼만 필터를 사용한 하모닉스 추정 방법에서 발생하는 발산 문제를 해결할 수 있다. 그것은 유일한 필터 구간 내에서 BIBO 안정도를 향상 보장하는 FIR필터의 구조에서 야기된다. 한편 기존의 하모닉스 추정 방법들과 여러 가지 측면의 성능 비교가 있었고 시뮬레이션 예제를 통해 본 논문에서 제시한 방법의 효용성을 입증하였다.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.4
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• pp.68-75
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• 2012

This paper presents a study on the driveline output torque estimation using a discrete Kalman filter. The in-situ output shaft torque is first measured by a non-contacting magneto-elastic torque transducer. The linear state-space system equations are first derived and the discrete Kalman filter is designed based on the Kalman filter theory to recover the driveline output torque contaminated by random noises. In addition to using torque measurement, the estimation of the output torque using two angular velocities: the output and wheel, is also conducted. The experimental results show that the discrete Kalman filter can be effective for not only removing the random noise in output torque but also estimating the output torque without torque measurement.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.2
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• pp.53-58
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• 2021

In this paper, an alternative finite memory structure(FMS) smoothing filter is developed for discrete-time state-space model with a control input. To obtain the FMS smoothing filter, unbiasedness will be required beforehand in addition to a performance criteria of minimum variance. The FMS smoothing filter is obtained by directly solving an optimization problem with the unbiasedness constraint using only finite measurements and inputs on the most recent window. The proposed FMS smoothing filter is shown to have intrinsic good properties such as deadbeat and time-invariance. In addition, the proposed FMS smoothing filter is shown to be equivalent to existing FMS filters according to the delay length between the measurement and the availability of its estimate. Finally, to verify intrinsic robustness of the proposed FMS smoothing filter, computer simulations are performed for a temporary model uncertainty. Simulation results show that the proposed FMS smoothing filter can be better than the standard FMS filter and Kalman filter.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.3
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• pp.219-226
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• 1992

In this study, Kalman filtering theory is applied to the estimation of symmetrical components from fault voltage and current signal when it comes to faults with the power system. An algorithm for estimating fault location accurately and quickly by calculating the symmetrical components from the extracted fundamental voltage phasor and current phasor is presented. Also, to confirm the validity of digital distance relaying techniques using Kalman filtering, the experimental results obtained by using the digital simulation of power system is shown.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.253-255
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• 2004

Conventional magnetic levitation systems could show unsatisfactory performance under air-gap disturbance due to rail irregularities. In this paper, we propose a feedback control system with discrete Kalman filter for air-gap disturbance attenuation. It is shown that excellent system performance can be obtained with the use of discrete Kalman filter, and that results from experiments agree well with those of simulations.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.7
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• pp.444-451
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• 2004

Conventional magnetic levitation systems could show unsatisfactory performance under air-gap disturbance due to rail irregularities. In this paper, we propose a feedback control system with discrete Kalman filter for air-gap disturbance attenuation. It is shown that excellent system performance can be obtained with the use of discrete Kalman filter, and that results from experiments agree well with those of simulations.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.958-961
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• 2008

본 논문은 옥내측위 결과에 지도정합 방법을 적용하는 실험 결과를 소개한다. 사용한 지도정합 방법은 측위 결과로 얻은 측정 궤적에 칼만필터를 적용하여 매끄러운 칼만필터궤적을 얻은 다음, 칼만필터궤적과 이산크레쉐거리가 가장 가까운 보행자 통로로 정합한다. 사용한 지도정합 방법의 효율성을 보이는 실험 결과도 소개한다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.10
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• pp.1057-1065
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• 1990

A parallel processing algorithm for the discrete Kalman filter, which is one of the most commonly used filtering techniques in modern control, signal processing, and communication, is proposed. To decrease the number of computations critical in the Kalman filter, previously proposed parallel algorithms are of the hierarchical structure by distributed processing of measurements, or of the systolic structure to disperse the computational burden. In this paper, a new parallel Kalman filter employing a structure similar to recursive doubling is proposed. Estimated valuse of state variables by the new algorithm converge faster to the true values because the new algorithm can process data twice faster than the conventional Kalman filter. Moreover, it maintains the optimality of the conventional Kalman filter.