• 대한의용생체공학회:의공학회지
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• 제27권3호
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• pp.131-141
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• 2006

A visual decision by clinical experts like physical therapists is a best way to detect onset and offset time of muscle activation. The current computer-based algorithms are being researched toward similar results of clinical experts. The new algorithm in this paper has an ability to extract a trend from noisy input data. Kalman smoother is used to recognize the trend to be revealed from disorderly signals. Histogram of smoothed signals by Kalman smoother has a clear boundary to separate muscle contractions from relaxations. To verify that the Kalman smoother algorithm is reliable way to detect onset and offset time of muscle contractions, the algorithm of Robert P. Di Fabio (published in 1987) is compared with Kalman smoother. For 31 templates of subjects, an average and a standard deviation are compared. The average of errors between Di Fabio's algorithm and experts is 109 milliseconds in onset detection and 142 milliseconds in offset detection. But the average between Kalman smoother and experts is 90 and 137 milliseconds in each case. Moreover, the standard deviations of errors are 133 (onset) and 210 (offset) milliseconds in Di Fabio's one, but 48 (onset) and 55 (offset) milliseconds in Kalman smoother. As a result, the Kalman smoother is much closer to determinations of clinical experts and more reliable than Di Fabio's one.

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.471-478
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• 2012

A foot motion is estimated using an inertial sensor unit, which is installed on a shoe. The inertial sensor unit consists of 3 axis accelerometer and 3 axis gyroscopes. Attitude and position of a foot are estimated using an inertial navigation algorithm. To increase estimation performance, a smoother is used, where the smoother employs a forward and backward filter structure. An indirect Kalman filter is used as a forward filter and backward filter. A new combining algorithm for the smoother is proposed to combine a forward indirect Kalman filter and a backward indirect Kalman filter. Through experiments, the estimation performance of the proposed smoother is verified.

• 한국지리정보학회지
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• 제13권2호
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• pp.157-167
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• 2010

언센티드 칼만 필터 기반의 역방향 필터를 유도하고 시뮬레이션 테스트를 통하여 확장 칼만 필터, 언센티드 칼만 필터, 그리고 확장 칼만 스무더로부터의 위치결과와 비교 분석하였다. 시뮬레이션은 GPS의 수신환경이 극단적으로 좋지 않을 경우를 고려하여 $40m{\times}40m $ 의 공간에서 4개의 곡선 그리고 5개의 직선구간으로 이루어진 궤적에서 시작점과 끝점만을 기지점으로 가정하여 수행하였다. 실험 결과 스무더는 순방향 필터에 비하여 최대 위치 오차값이 약 8~9m 정도 크게 감소하는 결과를 보여주었다. 스무더의 경우 위치오차를 직선구간과 곡선구간으로 나누어 분석하였는데, 언센티드 칼만 스무더가 확장 칼만 스무더에 비하여 직선 구간에서는 최대 10cm, 곡선 구간에서는 최대 23cm 향상된 결과를 나타내었다.

• Journal of Positioning, Navigation, and Timing
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• 제10권2호
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• pp.83-89
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• 2021

The extended Kalman filter (EKF) is widely used for global navigation satellite system (GNSS) applications. It is difficult to obtain precise positions with an EKF one-way (forward or backward) filter. In this paper, we propose an EKF smoother to improve the positioning accuracy by integrating forward and backward filters. For the EKF smoother experiment, we performed PPP using GNSS data received at the DAEJ reference station for a month. The effectiveness of the proposed approach is validated with multi-GNSS kinematic PPP experiments. The EKF smoother showed 35%, 6%, and 22% improvement in east, north, and up directions, respectively. In addition, accurate tropospheric zenith total delay (ZTD) values were calculated by a smoother. Therefore, the results from EKF smoother demonstrate that better accuracy of position can be achieved.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권2호
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• pp.245-254
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• 2004

이 논문은 카메라가 연속적으로 움직일 때 그 카메라로부터 얻은 동영상을 분석하여 카메라의 움직임에 대한 정보와 영상내의 구조물의 삼차원 정보를 계산하는 알고리듬에 대한 것이다. 일반적으로 불 연속한 위치에서 얻은 영상의 집합으로부터 삼차원정보 및 카메라 정보를 얻는 경우에는 카메라의 움직임에 대한 제약조건이 필요 없지만, 비디오 카메라를 이용하여 동영상을 취득하는 경우에는 항상 카메라의 움직임이 부드러워야 한다는 조건이 따라 붙는다. 따라서, 이 논문에서는 ‘부드러운 움직임을 가지는 카메라’라는 제약조건을 포함하는 카메라 및 삼차원정보의 최적화 과정에 대하여 연구하였다. 목적하는 바를 얻기 위하여 Expectation-Maximization 방법을 사용하여 카메라의 움직임에 대한 모델 파라메터를 동시에 추정하였는데, 이를 위하여 Extended Kalman Filter 와 Extended Kalman Smoother를 적용하였다. 이 연구는 길이가 긴 비디오 영상열의 비젼 해석에 기본이 된다. 실제 영상을 이용하여 실험한 결과를 보였다.

• 제어로봇시스템학회논문지
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• 제21권9호
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• pp.807-810
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• 2015

In this paper, a finite impulse response(FIR) fixed-lag smoother is proposed for discrete-time nonlinear systems. If the actual state trajectory is sufficiently close to the nominal state trajectory, the nonlinear system model can be divided into two parts: The error-state model and the nominal model. The error state can be estimated by adapting the optimal time-varying FIR smoother to the error-state model, and the nominal state can be obtained directly from the nominal trajectory model. Moreover, in order to obtain more robust estimates, the linearization errors are considered as a linear function of the estimation errors. Since the proposed estimator has an FIR structure, the proposed smoother can be expected to have better estimation performance than the IIR-structured estimators in terms of robustness and fast convergence. Additionally the proposed method can give a more general solution than the optimal FIR filtering approach, since the optimal FIR smoother is reduced to the optimal FIR filter by setting the fixed-lag size as zero. To illustrate the performance of the proposed method, simulation results are presented by comparing the method with an optimal FIR filtering approach and linearized Kalman filter.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2516-2520
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• 2005

In this paper, finite impulse response (FIR) smoothers are proposed for discrete-time systems. The proposed FIR smoother is designed under the constraints of linearity, unbiasedness, FIR structure, and independence of the initial state information. It is also obtained by directly minimizing the performance criterion with unbiased constraints. The approach to the MVF smoother proposed in this paper is logical and systematic, while existing results have heuristic assumption, such as infinite covariance of the initial state. Additionally, the proposed MVF smoother is based on the general system model that may have the singular system matrix and has both system and measurement noises. Thorough simulation studies, it is shown that the proposed MVF smoother is more robust against modeling uncertainties numerical errors than fixed-lag Kalman smoother which is infinite impulse response (IIR) type estimator.

• 제어로봇시스템학회논문지
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• 제8권11호
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• pp.984-990
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• 2002

We propose a new type of nonlinear fixed interval smoother to which an existing nonlinear smoother is modified. The nonlinear smoother is derived from two-filter formulas. For the backward filter. the propagation and the update equation of error states are derived. In particular, the modified update equation of the backward filter uses the estimated error terms from the forward filter. Data fusion algorithm, which combines the forward filter result and the backward filter result, is altered into the compatible form with the new type of the backward filter. 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 algorithm to off-line navigation system and show the proposed algorithm estimates position, and altitude fairly well through the computer simulation.

• 제어로봇시스템학회논문지
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• 제20권1호
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• pp.1-5
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• 2014

In this paper, we propose an optimal fixed-lag FIR (Finite-Impulse-Response) smoother for a class of discrete time-varying state-space signal models. The proposed fixed-lag FIR smoother is linear with respect to inputs and outputs on the recent finite horizon and estimates the delayed state so that the variance of the estimation error is minimized with the unbiased constraint. Since the proposed smoother is derived with system inputs, it can be adapted to feedback control system. Additionally, the proposed smoother can give more general solution than the optimal FIR filter, because it reduced to the optimal FIR filter by setting the fixed-lag size as zero. A numerical example is presented to illustrate the performance of the proposed smoother by comparing with an optimal FIR filter and a conventional fixed-lag Kalman smoother.

• 대한조선학회논문집
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• 제38권4호
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• pp.30-38
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• 2001

조류를 고려한 조종운동방정식을 정립한 후 선박의 운동변수 뿐만 아니라 외력 및 조류의 방향과 속도도 상태변수로 설정하여 비선형 상태방정식과 측정방정식을 표현하였다. 여기서 외력은 3차의 Gauss-Markov 프로세스로 표시하고, 조류의 방향과 속도는 일정하다고 가정하였다. 상태 추정을 위하여 확장 Kalman-Bucy 필터와 고정간격 스무더를 이용하였다. 기존의 Hwang은 실선 시운전 계측값을 이용하여 동유체력미계수 및 조류의 영향을 동시에 확장 Kalman 필터를 이용하여 추정하였으므로 매개변수의 개수가 상당히 많아지는 반면 모델링 전 추정기법을 사용하면 각각의 동유체력미계수를 추정하는 대신에 3방향의 외력과 조류 변수만을 추정한다. 측정잡음이 포함된 시뮬레이션 측정값을 적용하여 조류 변수를 추정하는 경우 실제값이 잘 추정되는 것을 확인하였다.