• 제어로봇시스템학회논문지
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• 제20권3호
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• pp.372-379
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• 2014

This paper surveys past and state-of-the-art SLAM technologies. The standard methods for solving the SLAM problem are the Kalman filter, particle filter, graph, and bundle adjustment-based methods. Kalman filters such as EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter) have provided successful results for estimating the state of nonlinear systems and integrating various sensor information. However, traditional EKF-based methods suffer from the increase of computation burden as the number of features increases. To cope with this problem, particle filter-based SLAM approaches such as FastSLAM have been widely used. While particle filter-based methods can deal with a large number of features, the computation time still increases as the map grows. Graph-based SLAM methods have recently received considerable attention, and they can provide successful real-time SLAM results in large urban environments.

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2011년도 한국우주과학회보 제20권1호
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• pp.25.4-25.4
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• 2011

Various estimation methods based on Kalman filter have been applied to the real-time satellite orbit determination. The most popular method is the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). The EKF is easy to implement and to use on orbit determination problem. However, the linearization process of the EKF can cause unstable solutions if the problem has the inaccurate reference orbit, sparse or insufficient observations. In this case, the UKF can be a good alternative because it does not contain linearization process. However, because both methods are based on Gaussian assumption, performance of estimation can become worse when the distribution of state parameters and process/measurement noise are non-Gaussian. In nonlinear/non-Gaussian problems the particle filter which is based on sequential Monte Carlo methods can guarantee more exact estimation results. This study develops and tests the particle filter for satellite orbit determination. The particle filter can be more effective methods for satellite orbit determination in nonlinear/non-Gaussian environment.

• 로봇학회논문지
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• 제9권4호
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• pp.216-224
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• 2014

This paper compares methods for attitude estimation of a UUV(Unmanned Underwater Vehicle). Attitude estimation plays a key role in underwater navigation using DVL(Doppler Velocity Log). The paper proposes attitude estimation methods using EKF(Extended Kalman Filter), UKF(Unscented Kalman Filter), and CF(Complementary Filter). It derives methods using the measurements from MEMS-AHRS(Microelectromechanical Systems-Attitude Heading Reference System) and DVL. The methods are used for navigation in a test pool and their navigation performance is compared. The results suggest that even if there is no measurement relative to some absolute landmarks, DVL-only navigation can be useful for navigation in a limited time and range.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.135-135
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• 2022

In this study, we evaluated uncertainties in baseflow separation filter methods focusing on changes in recession constant (𝛼) values, which include Lynie & Holick (LH) algorithm, Chapman algorithm, Eckhardt filter, and EWMA filter. Here, we analyzed daily streamflow data at 14 stations in the Urmia Lake basin, Iran, from 2015 to 2019. The 𝛼 values were computed using three different approaches from calculating the slope of a recession curve by averaging the flow over all seasons, a correlation method, and a mean value of the ratio of Q_t+1 to Q_t. In addition to the 𝛼 values, the BFImax (maximum value of the baseflow index (BFI)) was determined for the Eckhardt filter through the backward filter method. As results, it indicates that the estimated baseflow is dependent upon the selection of filter methods, their parameters, and catchment characteristics at different stations. In particular, the EWMA filter showed the least changes in estimating the baseflow value by changing the 𝛼 value, and the Eckhardt filter and LH algorithm showed the highest sensitivity to this parameter at different stations.

• Journal of Positioning, Navigation, and Timing
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• 제5권1호
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• pp.1-9
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• 2016

Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

• 한국전자통신학회논문지
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• 제3권4호
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• pp.282-288
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• 2008

본 연구에서는 고출력 RF 필터의 도금상태에 따른 수동혼변조왜곡(PIMD)을 측정하였으며 RF-filter의 PIMD를 저감시키기 위한 방안을 제시하였다. PIMD의 표준측정방안에 따라 Wibro 중계기용 고출력 RF-필터의 PIMD 특성를 측정하였다. Wibro용 고 전력-RF 필터의 설계에서 통과대역의 에지(edge)에서 삽입손실 및 지연 특성의 평탄도가 저하될 경우, PIMD의 발생되므로 본 연구에서는 고 전력 필터의 PIM을 감소시키기 위하여 필터의 내부 도금 재료의 종류와 방안을 제시하였다.

• 한국통신학회논문지
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• 제21권5호
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• pp.1155-1171
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• 1996

본 논문에서는 선행 연구한 Pseudomedian 필터를 토대로 하여 이의 특성을 종합적으로 분석, 비교하였다. 제안된 Psedomedian 필터는 H-shaped와 Asterisk-shaped 윈도우 타입으로 구분된다. 먼저 Pseudomedian 필터의 정의와 De-Interlacing Scan Conversion을 위한 Pseudomedian 필터 알고리즘에 대하여 논하고 이의 특성, 즉 Pseudomedian 필터의 에지 재현특성, 알고리즘에 근거하여 기존의 방식들과 연산량을 비교하였다. 그리고 PSNR이 pseudomedian 필터방식과 기존의 방식을 평가하기 위하여 이용되었다. 마지막으로, Pseudomedian 필터방식의 특징과 trade off에 대하여 논하였으며, 시스템 적용시의 잇점과 적용분야를 제시하였다.

• 공학논문집
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• 제3권1호
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• pp.43-46
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• 1998

지난 30년간 부가 잡음에 의해 열화된 음성신호의 개선에 관해 많은 연구가 진행되어 왔다. 잡음제거를 위한 고전적인 방법인 spectral subtraction, Wiener filter와 최근에 제안된 심리음향모델에 근거한 perceptual filter, EVRC의 잡음제거단을 성능과 구현의 복잡도 측면에서 비교하였다.

• Nuclear Engineering and Technology
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• 제26권2호
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• pp.205-211
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• 1994

로듐 자기출력형 중성자계측기에 대하여 3가지 디지탈 동적 보상방법을 개발 및 적용하여 가장 우수한 방법을 제시하였다. 3가지 디지탈 동적 보상방법은 기존 COLSS의 Dominant POL Tustin 방법과 Direct Inversion 방법 및 Kalman Filter 방법이다. 이 논문에서는 D. Hoppe와 R. Maletti의 Direct Inversion 방법을 개선하였으며 Kalman Filter를 이용한 방법을 개발하였다. 3가지 방법론을 비교한 결과 같은 Noise 중가 조건하에서 Step 중성자속 입력에 대한 90% 도달 시간이 각각 28.1초, 17.2초 및 6.5초로 나타나 Kalman Filter 방법이 가장 우수함을 알 수 있었다.

• International Journal of Aeronautical and Space Sciences
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• 제14권1호
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• pp.85-90
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• 2013

This paper presents a study on terrain referenced navigation (TRN). The extended Kalman filter (EKF) is adopted as a filter method. A Jacobian matrix of measurement equations in the EKF consists of terrain slope terms, and accurate slope estimation is essential to keep filter stability. Two slope estimation methods are proposed in this study. Both methods are based on the least-squares approach. One is planar regression searching the best plane, in the least-squares sense, representing the terrain map over the region, determined by position error covariance. It is shown that the method could provide a more accurate solution than the previously developed linear regression approach, which uses lines rather than a plane in the least-squares measure. The other proposed method is weighted planar regression. Additional weights formed by Gaussian pdf are multiplied in the planar regression, to reflect the actual pdf of the position estimate of EKF. Monte Carlo simulations are conducted, to compare the performance between the previous and two proposed methods, by analyzing the filter properties of divergence probability and convergence speed. It is expected that one of the slope estimation methods could be implemented, after determining which of the filter properties is more significant at each mission.