• Journal of Positioning, Navigation, and Timing
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• 제9권2호
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• pp.99-115
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• 2020

Since GNSS is easily affected by jamming and/or spoofing, alternative navigation systems can be operated as backup system to prepare for outage of GNSS. Alternative navigation systems are being researched over the world, and a multi-radio integrated navigation system using alternative navigation systems such as KNSS, eLoran, Loran-C, DME, VOR has been researched in Korea. Least Square or Kalman filter can be used to estimate navigation parameters in the navigation system. A large number of measurements of the Kalman filter may lead to heavy computational load. The decentralized Kalman filter and the federated Kalman filter were proposed to handle this problem. In this paper, the decentralized Kalman filter and the federated Kalman filter are designed for the multi-radio integrated navigation system and the performance evaluation result are presented. The decentralized Kalman filter and the federated Kalman filter consists of local filters and a master filter. The navigation parameter is estimated by local filters and master filter compensates navigation parameter from the local filters. Characteristics of three Kalman filters for a linear system and nonlinear system are investigated, and the performance evaluation results of the three Kalman filters for multi-radio integrated navigation system are compared.

• 한국시뮬레이션학회논문지
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• 제27권3호
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• pp.99-107
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• 2018

본 논문에서는 비선형성을 가지는 측정방정식의 상태값을 효과적으로 추정할 수 있는 확장칼만필터(Extended Kalman Filter/EKF)와 확장칼만필터의 변종들 그리고 코스트 레퍼런스 파티클필터(Cost-Reference Particle Filter/CRPF)를 이용하여 이차원 공간에서 표적추적 성능에 관하여 연구한다. 확장칼만필터의 변종으로 분산점칼만필터(Unscented Kalman Filter/UKF), 중심차분칼만필터(Central Difference Kalman Filter/CDKF), 제곱근 분산점칼만필터(Square Root Unscented Kalman Filter/SR-UKF) 그리고 제곱근 중심차분칼만필터(Square Root Central Difference Kalman Filter/SR-CDKF)를 소개한다. 본 연구에서는 노이즈가 불확실한 표적에 대하여 몬테카를로 시뮬레이션 기법을 이용하여 각 필터들의 평균제곱오차(Mean Square Error/MSE)를 계산하였다. 시뮬레이션 결과 확장칼만필터의 변종들 중에서 제곱근 중심차분칼만필터가 속도와 성능 면에서 가장 우수한 결과를 보여주었다. 코스트 레퍼런스 파티클 필터는 확장칼만필터와 다르게 노이즈의 확률 분포를 알 필요가 없다는 유리한 특성을 가지고 있으며 시뮬레이션 결과 제곱근 중심차분칼만필터보다 처리속도 및 정확도 면에서 우수한 결과를 보여주었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.39.3-39
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• 2001

Since Kalman filter and wavelet transform techniques are both suitable for a nonstationary process, wavelet-Kalman filter was proposed and applied to various industrial fields. However, the wavelet-Kalman filter subjected to model uncertainty with nonstationary process has not been considered. Thus, the robust wavelet-Kalman filter method is proposed in this paper. The proposed method can prevent the degradation of filter performance when parameter uncertainty exists in both the state and measurement matrices and preserve the merits of the standard Kalman filter in the sense that it produces optimal estimates. A simple example shows that the proposed approach outperforms the standard Kalman filter and the nominal wavelet-Kalman filter.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.353-356
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• 2011

본 연구에서는 G/R 비의 실시간 결정을 목적으로 Dual Kalman Filter를 이용하였다. Dual Kalman Filter 는 이중추정(dual estimation)을 기반으로 하는 자료동화기법으로 기존 Kalman Filter와 상이한 상태-공간 모형으로 구성된다. 이에 Dual Kalman Filter와 기존 Kalman Filter의 적용성능을 비교 검토하였으며, 다양한 비교를 위하여 강우의 임계치와 누적시간의 고려여부에 따른 결과를 추가적으로 검토하였다. 두 기법의 적용성능 비교결과 Dual Kalman Filter가 우수한 것으로 나타났다. 이는 Dual Kalman Filter 기법이 G/R 비의 큰 변동성과 이상치를 효과적으로 필터링하고, 시계열 모형의 매개변수를 실시간으로 갱신하여 정확한 예측치를 추정하였기 때문인 것으로 판단된다.

• 한국환경과학회지
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• 제3권4호
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• pp.349-356
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• 1994

The purpose of this study is to develop a linear reservoir model with Kalman filter using Kalman filter theory which removes a physical uncertainty of :ainfall-runoff process. A linear reservoir model, which is the basic model of Kalman filter, is used to calculate runoff from rainfall in river basin. A linear reservoir model with Kalman filter is composed of a state-space model using a system model and a observation model. The state-vector of system model in linear. The average value of the ordinate of IUH for a linear reservoir model with Kalman filter is used as the initial value of state-vector. A .linear reservoir model with Kalman filter shows better results than those by linear reserevoir model, and decreases a physical uncertainty of rainfall-runoff process in river basin.

• 전기학회논문지
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• 제65권6호
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• pp.1019-1025
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• 2016

This paper proposes a parallel reduced-order square-root unscented Kalman filter for state estimation of a sensorless permanent-magnet synchronous motor. The appearance of an unscented Kalman filter is caused by the linearization process error between a real system and classical Kalman model. The unscented transformation can make a more accurate Kalman model. However, the complexity is its main drawback. This paper investigates the design and implementation of the proposed filter with Potter and Carlson square-root form. The proposed parallel reduced-order square-root unscented Kalman filter reduces memory and code size, and improves numerical computation. And the performance is not significantly different from the unscented Kalman filter. The experimentation is performed for the verification of the proposed filter.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.973-978
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• 2005

In this paper, we investigate an improved mobile robot localization method using Kalman filter. The highlight of the paper lies in the formulation of combined Kalman filter and its application to mobile robot experiment. The combined Kalman filter is a kind of extended Kalman filter which has an extra degree of freedom in Kalman filtering recursion. It consists of the standard Kalman filter, i.e., the predictor-corrector and the perturbation estimator which reconstructs unknown dynamics in the state transition equation of mobile robot. The combined Kalman filter (CKF) enables to achieve robust localization performance of mobile robot in spite of heavy perturbation such as wheel slip and doorsill crossover which results in large odometric errors. Intrinsically, it has the property of integrating the innovation in Kalman filtering, i.e., the difference between measurement and predicted measurement and thus it is so much advantageous in compensating uncertainties which has not been reflected in the state transition model of mobile robot. After formulation of the CKF recursion equation, we show how the design parameters can be determined and how much beneficial it is through simulation and experiment for a two-wheeled mobile robot under indoor GPS measurement system composed of four ultrasonic satellites. In addition, we discuss what should be considered and what prerequisites are needed to successfully apply the proposed CKF in mobile robot localization.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 1998년도 공동추계학술대회 경제위기 극복을 위한 정보기술의 효율적 활용
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• pp.757-764
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• 1998

본 논문에서는 Glover-Doyle의 H$\infty$ 설계기법을 이용하여 H$\infty$ 성능경계를 만족하는 Kalman 필터를 설계하는 방법을 제시한다. 제시한 방법을 사용하면, kalman 필터의 성능 강인성과 안정화 강인성 문제와의 관계를 설계변수의 설정으로 설계자가 적절하게 선택함으로써 구조적 불확실성에 대하여 비교적 강인한 H$\infty$ -norm Kalman 필터를 설계할 수 있도록 한다. 설계의 예를 통하여 H$\infty$ -norm Kalman 필터의 설게방법을 보이고, H2-norm Kalman 필터와 비교함으로써 제시된 방법이 특성을 보인다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 D
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• pp.2335-2337
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• 2004

Kalman filter를 필터링에 적용할 때에 센서의 아날로그 신호에 들어오는 측정값의 잡음은 Gaussian 확률분포를 갖는다고 가정한다. 그러나 Kalman filter를 digital 컴퓨터에 적용할 경우에는 analog-to-digital converter에서 측정값의 잡음이외에도 quantization 잡음이 존재하며 본 논문에서는 이러한 경우에 quantization 영향이 Kalman filter 알고리듬에 미치는 영향을 수치적으로 분석하여 quantization을 Kalman filter 구현에 고려해야 될 사항으로 분류하고자 한다.

• Communications for Statistical Applications and Methods
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• 제25권1호
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• pp.99-107
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• 2018

This article considers a robust Kalman filter from the M-estimation point of view. Pak (Journal of the Korean Statistical Society, 27, 507-514, 1998) proposed a particular M-estimating function which has the data-based shaping constants. The Kalman filter with the proposed M-estimating function is considered. The structure and the estimating algorithm of the Kalman filter accompanying the M-estimating function are mentioned. Kalman filter estimates by the proposed M-estimating function are shown to be well behaved even when data are contaminated.