• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.798-802
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper, the robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is to use different models (CAD model etc.) known a priori. Also fusion of multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Because voting is a very simple or no model is needed for fusion, voting-based fusion of cues is applied. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters, namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.332-334
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• 1994

This paper proposes a robust active noise control (ANC) system. The system constructs filter with a standard model. An adaptive litter, connected to the system in parallel, compensates the modeling error. When the adaptive filter does not work, the proposed system is robust while the conventional system loses the noise control capability. But proposed ANC system shows that the performance is comparable with that of the conventional ANC system under normal conditions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.1961-1963
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• 2001

In a target tracking problem, the radar glint noise has non-Gaussian heavy-tailed distribution and will seriously affect the target tracking performance. In this study, an extended robust $H_{\infty}$ was developed which can significantly improve the tracking performance when glint noise is present. Through the computer simulations, the proposed filter showed superior and robust tracking performance compared with other extended Kalman filters.

• 전기학회논문지
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• 제61권2호
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• pp.276-283
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• 2012

In this paper, a practical quasi-optimal DOA(direction of arrival) estimator is proposed in order to develop a one-axis gimbaled ultrasonic source tracker for mobile robot applications. With help of the gimbal structure, the ultrasonic moving source tracking problem can be simply reduced to the DOA estimation. The DOA estimation is known as one of the representative long-pending nonlinear filtering problems, but the conventional nonlinear filters might be restrictive in many actual situations because it cannot guarantee the reliable performance due to the use of nonlinear signal model. This motivates us to reformulate the DOA estimation problem in the linear robust state estimation setting. Based on the assumption that the received ultrasonic signals are noisy sinusoids satisfying linear prediction property, a linear uncertain measurement model is newly derived. To avoid the DOA estimation performance degradation caused by the stochastic parameter uncertainty contained in the linear measurement model, the recently developed NCRKF (non-conservative robust Kalman filter) scheme [1] is utilized. The proposed linear DOA estimator provides excellent DOA estimation performance and it is suitable for real-time implementation for its linear recursive filter structure. The effectiveness of the suggested DOA estimation scheme is demonstrated through simulations and experiments.

• 한국지능시스템학회논문지
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• 제12권2호
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• pp.115-122
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• 2002

본 논문에서는 웨이블렛 서브밴드 필터링기법을 이용하여 다중의사 결정기법에 기반을 둔 외부 잡음에 강인한 고립단어 음성인식 알고리즘을 제안하고자 한다. 음성인식에 있어서 외부잡음은 음성인식 알고리듬의 인식률을 저하시키는 주요 원인으로 지적되므로 음성인식기의 성능을 향상시키기 위해서 무엇보다도 잡음에 강인한 음성인식 알고리즘의 개발이 절실히 요구되고 있다. 제안된 알고리즘의 타당성을 검증하기 위하여 다양한 자동차 소음하에서 한국어 단독 숫자음 10단어의 인식률 변동을 알아 보았다. 그 결과 현재 음성인식 기법으로 널리 쓰이고 있는 벡터양자화 알고리즘만을 적용한 경우에 비해 9~25%의 향상된 인식률을 보였다.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1357-1368
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• 2017

The lack of controllability over the wind causes fluctuations in the output power of the wind generators (WGs) located at the wind farms. Distribution Static Compensator (DSTATCOM) equipped with Battery Energy Storage System (BESS) can significantly smooth these fluctuations by injecting or absorbing appropriate amount of active power, thus, controlling the power flow of WGs. But because of the component aging and thermal drift, its harmonic filter parameters vary, resulting in performance degradation. In this paper, Quantitative Feedback Theory (QFT) is used as a robust control scheme in order to deactivate the effects of filter parameters variations on the wind power generation power smoothing performance. The proposed robust control strategy of the DSTATCOM is successfully applied to a microgrid, including WGs. The simulation results obviously show that the proposed control technique can effectively smooth the fluctuations in the wind turbines' (WT) output power caused by wind speed variations; taking into account the filter parameters variations (structural parameter uncertainties).

• Journal of the Optical Society of Korea
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• 제13권1호
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• pp.116-122
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• 2009

In this paper, a robust method is developed to locate the irises of both eyes. The method doesn't put any restrictions on the background. The method is based on the AdaBoost algorithm for face and eye candidate points detection. Candidate points are tuned such that two candidate points are exactly in the centers of the irises. Mean crossing function and convolution template are proposed to filter out candidate points and select the iris pair. The advantage of using this kind of hybrid method is that AdaBoost is robust to different illumination conditions and backgrounds. The tuning step improves the precision of iris localization while the convolution filter and mean crossing function reliably filter out candidate points and select the iris pair. The proposed structure is evaluated on three public databases, Bern, Yale and BioID. Extensive experimental results verified the robustness and accuracy of the proposed method. Using the Bern database, the performance of the proposed algorithm is also compared with some of the existing methods.

• 전기학회논문지
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• 제67권2호
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• pp.314-324
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• 2018

This paper proposes a linear distributed target tracking filter for multiple unmanned aerial vehicles(UAVs) sharing their passive sensor measurements through communication channels. Different from the conventional nonlinear filtering schemes, the distributed passive target tracking problem is newly formulated within the framework of a linear robust state estimation theory incorporated with a linear uncertain measurement equation including the coordinate transform uncertainty. To effectively cope with the performance degradation due to the coordinate transform uncertainty, a linear consistent robust Kalman filter(CRKF) theory is devised and applied for designing a distributed passive target tracking filter. Through the simulations for typical UAV surveillance mission, the superior performance of the proposed method over the existing schemes of distributed passive target tracking are demonstrated.

• 제어로봇시스템학회논문지
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• 제7권8호
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• pp.703-710
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• 2001

The nonlinear observers are proposed for a nonlinear system. To improve the characteristics such as stability, convergence, and $H^{\infty}$ filter performance criterion, we utilize an $H^{\infty}$ filter Riccati equation or a modified $H^{\infty}$ filter Riccati equation with a freedom parameter. Using the Lyapunov function method, the characteristics of the observers are analyzed. Then the in-flight alignment for a strapdown inertial navigation system(SDINS) is designed using the proposed observer. And the additive quaternion error model is especially used to reduce the uncertainty of the SDINS error model. Simulation results show that the observer with the modified $H^{\infty}$ filter Riccati equation effectively improves the performance of the in-flight alignment.

• 한국멀티미디어학회논문지
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• 제10권1호
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• pp.26-35
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• 2007

본 논문은 연속적으로 입력되는 비디오 영상에서 효과적인 얼굴 검출기와 칼만 필터를 이용하여 강인하게 얼굴을 추적하는 시스템을 제안한다. 효과적인 얼굴 검출기를 구성하기 위해 간단한 다섯 가지 타입의 Haar-like 특징값들을 이용하여 얼굴 특징을 추출한다. 추출된 특징값들은 PCA(Principal Component Analysis)를 이용하여 재해석되고, 해석된 주성분들을 SVM(Support Vector Machine)의 입력 값으로 사용하여 얼굴과 배경으로 분류한다. 검출된 얼굴의 정적정보와 프레임간 변화량을 이용한 동적정보를 칼만 필터(Kalman Filter)에 적용하여 얼굴을 추적한다. 실시간에 적용 가능한 시스템을 구현하기 위하여 얼굴 검출회수를 조정하여 처리속도를 향상시켰다. 실험결과, 평균 93.3%의 추적 성공률과 초당 15 프레임 처리 성능으로 강인한 실시간 얼굴 추적이 가능함을 보여주었다.