• 제어로봇시스템학회논문지
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• 제19권5호
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• pp.481-487
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• 2013

This paper presents an FIR (Finite Impulse Response) fixed-interval smoothing filter for fast and exact estimating state variables of a discrete nonlinear system with modeling uncertainty. Conventional IIR (Infinite Impulse Response) filter and smoothing filter can estimate state variables of a system with an exact model when the system is observable. When there is an uncertainty in the system model, however, conventional IIR filter and smoothing filter may cause large errors because the filters cannot estimate the state variables corresponding to the uncertain model exactly. To solve this problem, FIR filters that have fast estimation properties and have robustness to the modeling uncertainty have been developed. However, there is time-delay estimation phenomenon in the FIR filter. The FIR smoothing filter proposed in this paper makes up for the drawbacks of the IIR filter, IIR smoothing filter, and FIR filter. Therefore, the FIR smoothing filter has good estimation performance irrespective of modeling uncertainty. The proposed FIR smoothing filter is applied to the integrated navigation system composed of a magnetic compass based DR (Dead Reckoning) and a GPS (Global Positioning System) receiver. Even when the magnetic compass error that changes largely as the surrounding magnetic field is modeled as a random constant, it is shown that the FIR smoothing filter can estimate the varying magnetic compass error fast and exactly with simulation results.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제10권2호
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• pp.53-58
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• 2021

본 논문에서는 제어 입력이 있는 이산 시간 상태 공간 모델에 대한 유한기억구조(Finite Memory Structure, FMS) 스무딩 필터(Smoothing filter)를 개발한다. FMS 스무딩 필터는 가장 최근 윈도우의 유한 관측값과 제어 입력값만을 이용하여 비편향성 제약조건하에서 최소 분산 성능 지표의 최적화 문제를 직접 해결함으로써 얻어진다. FMS 스무딩 필터는 비편향성(Unbiasedness), 무진동성(Deadbeat) 및 시불변성(Time-invariance)과 같은 내재적으로 좋은 특성을 갖는다. 또한, 관측값과 추정값이 구해지는 시간 사이의 지연 길이에 따라 FMS 스무딩 필터는 기존의 FMS 필터들과 동등함을 보인다. 마지막으로, 컴퓨터 시뮬레이션을 통해 제안된 FMS 스무딩 필터의 내재적인 강인성(Robustness)을 검증하기 위해 일시적인 모델 불확실성을 가진 시스템에 FMS 스무딩 필터를 적용해본다. 시뮬레이션 결과를 통해 제안된 FMS 스무딩 필터가 기존의 FMS 필터와 칼만(Kalman) 필터보다 우수할 수 있음을 보여준다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.177.4-177
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• 2001

In this paper, we propose a new type of nonlinear fixed interval smoothing filter which is modified from the existing nonlinear smoothing filter. A nonlinear smoothing filter is derived from two-filter formulas. For the backward filter, the propagation and update equation of error states are derived. Particularly the modified update equation of the backward filter use the estimated error terms from the forward filter. Smoothing algorithm is altered into the compatible form with the new type of the backward fitter. An advantage of the proposed algorithm is more efficient than the existing one because propagation in backward filter is very simple from the implementation point of view. We apply the proposed nonlinear smoothing ...

• 제어로봇시스템학회논문지
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• 제7권12호
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• pp.1015-1023
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• 2001

error behaviour can be considered as a linear combination of low amplitude random noise and abrupt jumps. The reason of jump appearance can be explained by the semi-shading effects(buildings, trees), jamming, high dynamic of vehicle and so on. This study describes the stand-alone GPS error jump smoothing algorithm which is developed based on the scalar adaptive filter. The algorithm consists of the coarse jump smoothing and the fine jump smoothing. On the coarse smoothing step, GPS velocities or position differences are used as the measurement for the scalar adaptive filter. The purpose of adaptive filter is to smooth the jump errors. The coarse positions are detennined by the integration of smoothed velocities. On the fine smoothing step, the differences between GPS positions and the coarse positions are smoothed by another scalar adaptive filter. The reason of fine smoothing is based on the facts that smoothing accuracy depends on the variance ofusefuJ signa\. The coarse smoothing which deal with the difference of positions provides the rough error removing. So the coarse smoothed velocities can have much more low amplitude than the raw ones. The fine smoothing procedure provides high quality of filtering process. Simulation results show the efficiency of proposed scheme.

• 대한전자공학회논문지
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• 제20권4호
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• pp.1-9
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• 1983

MRAS 초안주 출력 오차 모델(MRAS hyperstable output-error model)을 이용한 적응 순환 필터(adaptive recursive filter)의 설계상 가장 어려운 점은 오차 완화 필터 (error-smoothing filter)의 설계이다. 본 논문에서는 적응 순환 필터의 대표적 알고리즘인 HARF(hyperstable adaptive recursive filter) 알고리즘을 적절히 변형시킴으로써 오차 완화 필터를 제거시킬 수 있고, 동시에 수산 속도도 바른 알고리즘을 얻을 수 있음을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.56.3-56
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• 2001

This study describes the jump error smoothing scheme with fuzzy logic based on the scalar adaptive filter. The scalar adaptive filter is an useful algorithm for smoothing abrupt jump errors. However, the performances of scalar adaptive algorithm depend on the variance of real signal. So to design an effective algorithm, many informations of real and jump signal are required. In this paper, the fuzzy rules are designed by the analysis of scalar adaptive filter, and then the improved and simplified scheme is developed for smoothing the jump error. Simulations to INS/GPS integrated system show that the proposed method is effective.

• International Journal of Aeronautical and Space Sciences
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• 제18권1호
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• pp.118-128
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• 2017

In this study, we propose a real time inertial navigation system/global positioning system (INS/GPS) integrated smoothing algorithm based on an extended Kalman filter (EKF) and a position damping loop (PDL) for synthetic aperture radar (SAR). Integrated navigation algorithms usually induce discontinuities due to error correction update by the Kalman filter, which are as detrimental to the performance of SAR as the relative position error. The proposed smoothing algorithm suppresses these discontinuities and also reduces the relative position error in real time. An EKF estimates the navigation errors and sensor biases, and all the errors except for the position error are corrected directly and instantly. A PDL activated during SAR operation period imposes damping effects on the position error estimates, where the estimated position error is corrected smoothly and gradually, which contributes to the real time smoothing and small relative position errors. The residual errors are re-estimated by the EKF to maintain the estimation performance and the stability of the overall loop. The performance improvements were confirmed by Monte Carlo simulations. The simulation results showed that the discontinuities were reduced by 99.8% and the relative position error by 48% compared with a conventional EKF without a smoothing loop, thereby satisfying the basic performance requirements for SAR operation. The proposed algorithm may be applicable to low cost SAR systems which use a conventional INS/GPS without changing their hardware configurations.

• 전력전자학회논문지
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• 제12권5호
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• pp.409-415
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• 2007

본 논문에서는 필터 설계시 고려해야 될 주요 항목 중 하나인 성능인자 권장값을 만족시키기 위해 단극 발전기의 내부인자 값을 필터 설계에 반영하는 새로운 평활필터 설계방법을 제안한다. 이 방법은 감쇄용 저항을 배제시킴으로서 평활필터의 효율증대 및 소형화를 기한다. 그리고 성능인자와 함께 공진주파수도 함께 고려함으로서 부성저항 특성을 갖는 고승압 변환기 등을 적용한 시스템의 안정성을 증대시킨다.

• 한국컴퓨터정보학회논문지
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• 제23권12호
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• pp.27-33
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• 2018

In this paper, we propose an efficient edge preserving smoothing filter for Infrared image that can reduce noise while preserving edge information. Infrared images suffer from low signal-to-noise ratio, low edge detail information and low contrast. So, detail enhancement and noise reduction play crucial roles in infrared image processing. We first apply a guided image filter as a local analysis. After the filtering process, we optimization globally using relativity of guided image filter. Our method outperforms the previous methods in removing the noise while preserving edge information and detail enhancement.

• 제어로봇시스템학회논문지
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• 제7권11호
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• pp.944-952
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• 2001

Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it is desired to combine INS with external aids such as GPS. However GPS informations have a randomly abrupt jump due to a sudden corruption of the received satellite signals and environment, and moreover GPS can\`t provide navigation solutions. In this paper, smoothing and prediction schemes are proposed for GPS`s jump or unavailable GPS. The smoothing algorithm which is designed as a scalar adaptive filter, smooths abrupt jump. The prediction algorithm which is proved by Schuler error model of INS, estimates INS error in appropriate time. The outputs of proposed algorithm apply stable measurements to GPS aided INS Kalman filter. Simulations show that the proposed algorithm can effectively remove measurement jump and predict INS error.