• 한국통신학회논문지
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• 제37권5B호
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• pp.370-376
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• 2012

CSS(Chirp Spread Spectrum)는 WPAN(Wireless Personal Area Network) 환경에서 SDS-TWR(Symmetric Double Sided - Two Way Ranging) 기반의 위치인식 시스템을 구현하는 기술로 사용된다. 그러나 CSS의 SDS-TWR은 전파 및 장애물과 같은 환경에 따른 간섭으로 인해 레인징 오차가 발생한다. 따라서 위치인식 시스템 개발을 위해서는 이를 보정하기 위한 보정 알고리즘이 요구된다. 본 논문은 위치인식 정확도 성능 향상을 위하여 AEDR(Algorithm of Equivalent Distance Rate) 알고리즘과 칼만필터가 적용된 KF_EDR(Kalman Filter and Equivalent Distance Rate) 보정 알고리즘을 제안하고, 그 성능을 분석 및 평가하였다. 실험 결과, KF_EDR은 AEDR 알고리즘에 비해 위치인식 정확도를 복도 그리고 운동장에서 각각 10.5%, 4.2% 더 개선시켰다. 이 결과는 위치인식 데이터의 신뢰성을 향상시킴 으로써 실제 위치인식 시스템 구현에 상당한 도움을 줄 수 있을 것으로 판단된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.3145-3162
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• 2023

As an important technology of the internetwork, wireless sensor network technique plays an important role in indoor localization. Non-line-of-sight (NLOS) problem has a large effect on indoor location accuracy. A location algorithm based on improved particle filter and directional probabilistic data association (IPF-DPDA) for WSN is proposed to solve NLOS issue in this paper. Firstly, the improved particle filter is proposed to reduce error of measuring distance. Then the hypothesis test is used to detect whether measurements are in LOS situations or NLOS situations for N different groups. When there are measurements in the validation gate, the corresponding association probabilities are applied to weight retained position estimate to gain final location estimation. We have improved the traditional data association and added directional information on the original basis. If the validation gate has no measured value, we make use of the Kalman prediction value to renew. Finally, simulation and experimental results show that compared with existing methods, the IPF-DPDA performance better.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.153-156
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• 1996

A new filtering algorithm for radar tracking is developed based on the fact that correct evaluation of the measurement error covariance can be made possible by doing it with respect to the Cartesian state vector. The new filter may be viewed as a modification of the extended Kalman filter where the variance of the range measurement errors is evaluated in an adaptive manner. The structure of the proposed filter allows sequential measurement processing scheme to be incorporated into the scheme, and this makes the resulting algorithm favorable in both estimation accuracy and computational efficiency.

• 전기학회논문지P
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• 제57권2호
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• pp.115-120
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• 2008

The EKF(Extended Kalman filter) method which is the state estimation algorithm of nonlinear stochastic system depends on the initial error and the estimated states. Therefore, the divergence of the estimated state can be caused if the initial values of the estimated states are not chosen as approximate real state values. In this paper, the demerit of the existing EKF method is improved using the EKF algorithm transformated by STWS(Single Term Walsh Series). This method linearizes each sampling interval of continous-time system through the derivation of an algebraic iterative equation without discretizing continuous system by the characteristic of STWS, the convergence of the estimated states can be improved. The validity of the proposed method is checked through comparison with the existing EKF method in simulation.

• Journal of Electrical Engineering and information Science
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• 제1권2호
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• pp.39-44
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• 1996

An efficient interacting multiple mode(IMM) approach for tracking a maneuvering target with kinematic constraints is described based on the square root information filter(SRIF). The SRIF is employed instead of the conventional Kalman filter since it exhibits more efficient features in handling the kinematic constraints and improved numerical characteristics. The kinematic constraints are considered in the filtering process as pseudomeasurements where the degree of uncertainty is represented by the magnitude of the pseudomeasurement noise variance. The Monte Carlo simulations for the constant speed, maneuvering target are provided to demonstrate the improved tracking performance of the proposed algorithm.

• 한국음향학회지
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• 제32권4호
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• pp.354-360
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• 2013

본 논문은 고밀도 클러터 환경에서 클러터 제거기능을 이용하여 구간선형기동 수중운동체의 탐지 및 추적에 대한 성능향상을 다루었다. 고밀도 클러터 환경에서 허프변환(Hough transform)을 이용한 클러터 제거 알고리즘을 통해 클러터 특성을 나타내는 측정치를 제거한 후 남은 측정치에 대해 추적 필터인 CMKF-L을 적용하여 추적성능을 확인하였다. 모의 신호와 해상실험데이터를 이용하여 실험을 수행하였으며 고밀도 클러터 환경에서 제안하는 알고리즘을 적용하여 클러터는 상당수 제거되고 표적에 대한 추적은 지속적으로 안정되게 수행됨을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.1757-1758
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• 2008

Extended Kalman Filter(EKF) is widely used in tracking position of nonlinear system. but there exists a divergence problem caused by approximation of nonlinear system's linearization. Adaptive fading Kalman filter (AFKF) is one of the effective methods which employs suboptimal fading factors to solve the divergence problem in an EKF In this paper we present an improved TDoA (time difference of arrival) based position tracking by using AFKF.

• 한국정밀공학회지
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• 제15권6호
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• pp.175-182
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• 1998

An advanced visual tracking and stable grasping algorithm for a moving object is proposed. The stable grasping points for a moving 2D polygonal object are obtained through the visual tracking system with the Kalman filter and image prediction technique. The accuracy and efficiency are improved more than any other prediction algorithms for the tracking of an object. In the processing of a visual tracking. the shape predictors construct the parameterized family and grasp planner find the grasping points of unknown object through the geometric properties of the parameterized family. This algorithm conducts a process of ‘stable grasping and real time tracking’.

• Journal of Power Electronics
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• 제12권1호
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• pp.40-48
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• 2012

This paper proposes the State-of-charge (SOC) estimator of a LiPB Battery using the Extended Kalman Filter (EKF). EKF can work properly only with an accurate model. Therefore, the high accuracy electrical battery model for EKF state is discussed in this paper, which is focused on high-capacity LiPB batteries. The battery model is extracted from a single cell of LiPB 40Ah, 3.7V. The dynamic behavior of single cell battery is modeled using a bulk capacitance, two series RC networks, and a series resistance. The bulk capacitance voltage represents the Open Circuit Voltage (OCV) of battery and other components represent the transient response of battery voltage. The experimental results show the strong relationship between OCV and SOC without any dependency on the current rates. Therefore, EKF is proposed to work by estimating OCV, and then is converted it to SOC. EKF is tested with the experimental data. To increase the estimation accuracy, EKF is improved with a single dominant varying parameter of bulk capacitance which follows the SOC value. Full region of SOC test is done to verify the effectiveness of EKF algorithm. The test results show the error of estimation can be reduced up to max 5%SOC.

• 한국정보통신학회논문지
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• 제20권5호
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• pp.998-1004
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• 2016

3상 PWM 컨버터는 입력 전류를 정현적으로 제어할 수 있어 입력 전류의 고조파 성분을 감소시킬 수 있고 입력 전압에 대하여 입력 전류의 위상을 제어할 수 있다. 본 논문은 3상 PWM 컨버터의 역률개선을 위하여 전원전압센서를 사용하지 않고 가상자속기반 벡터제어를 적용한 새로운 센서리스 제어방식을 연구하였다. 직류출력전압은 칼만 필터를 적용하여 추정한 가상자속에 의해 제어되며, 동기위상은 추정된 가상자속을 이용하여 위상을 얻는다. 제시한 PFC 알고리즘은 역률개선 및 가변영역에서 직류출력전압, 부하변동에서 직류출력전압을 정밀하게 제어할 수 있는 우수성을 가진다. 본 논문에서 제안한 가상자속추정 알고리즘을 적용한 칼만 필터 성능은 실험과 시뮬레이션을 통해서 검증하였다.