• Title/Summary/Keyword: 확장된 칼만필터

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A Parallel Kalman Filter for Estimation of Magnetic Disturbance and Orientation Based on Nine-axis Inertial/Magnetic Sensor Signals (9축 관성/자기센서를 이용한 자기교란 및 자세 추정용 병렬 칼만필터)

  • Lee, Jung Keun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.40 no.7
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    • pp.659-666
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    • 2016
  • Magnetic disturbance is one of the main factors that deteriorate the accuracy of orientation estimation methods based on inertial/magnetic sensor signals. This paper proposes a parallel Kalman filter(KF) that explicitly detects magnetic disturbances and thus can accurately estimate 3D orientation in magnetically disturbed environments. Due to the parallel nature of the proposed KF, even severe magnetic disturbances only affect yaw estimation, while roll and pitch values remain accurate. Consequently, the proposed KF can be effectively used in various applications that involve magnetically inhomogeneous environments, such as robots, ships, and planes.

EKF SLAM-based Camera Tracking Method by Establishing the Reference Planes (기준 평면의 설정에 의한 확장 칼만 필터 SLAM 기반 카메라 추적 방법)

  • Nam, Bo-Dam;Hong, Hyun-Ki
    • Journal of Korea Game Society
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    • v.12 no.3
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    • pp.87-96
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    • 2012
  • This paper presents a novel EKF(Extended Kalman Filter) based SLAM(Simultaneous Localization And Mapping) system for stable camera tracking and re-localization. The obtained 3D points by SLAM are triangulated using Delaunay triangulation to establish a reference plane, and features are described by BRISK(Binary Robust Invariant Scalable Keypoints). The proposed method estimates the camera parameters from the homography of the reference plane when the tracking errors of EKF SLAM are much accumulated. Using the robust descriptors over sequence enables us to re-localize the camera position for matching over sequence even though the camera is moved abruptly.

Real-Time Acquisition Method of Posture Information of Arm with MEMS Sensor and Extended Kalman Filter (MEMS센서와 확장칼만필터를 적용한 팔의 자세정보 실시간 획득방법)

  • Choi, Wonseok;Kim, HeeSu;Kim, Jaehyun;Cho, Youngki
    • The Journal of the Korea Contents Association
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    • v.20 no.6
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    • pp.99-113
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    • 2020
  • In the future, robots and drones for the convenience of our lives in everyday life will increase. As a method for controlling this, a remote control or a human voice method is most commonly used. However, the remote control needs to be operated by a person and can not ignore ambient noise in the case of voice. In this paper, we propose an economical attitude information acquisition method to accurately acquire the posture information of the arm in real time under the assumption that the surround drones or robots can be controlled wirelessly with the posture information of the arm. For this purpose, the extended Kalman filter was used to eliminate the noise of the arm position information. in order to detect the arm movement, a low cost MEMS type sensor was applied to secure the economical efficiency of the apparatus. To increase the wear ability of the arm, We developed a compact and lightweight attitude information acquisition system by integrating all functions into one chip as much as possible. As a result, the real-time performance of 1 ms was secured and the extended Kalman filter was applied to acquire the accurate attitude information of the arm with noise removed and display the attitude information of the arm in real time. This provides a basis for generating commands using real-time attitude information of the arm.

The Unscented Kalman Filter Based Backward Filters for the Precise INS/GPS System (정밀 INS/GPS시스템을 위한 언센티드 칼만 필터 기반의 역방향 필터연구)

  • Kwon, Jay-Hyoun;Lee, Jong-Ki;Lee, Ji-Sun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.2
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    • pp.157-167
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    • 2010
  • Unscented Kalman filter based backward filter is derived and the positions from extended Kalman filter, unscented Kalman filter, and extended Kalman smoother are compared and analyzed through a simulation test. Considering the poor GPS signal reception, the simulation is performed under the assumption of only the start and end points of the trajectory, composed of 4 curves and 5 straight sections in the area of $40m{\times}40m $, are known. The test shows that the smoothers generate much better positioning results of 8~9m improvement compared to those from the forward filters. For the comparison between the smoothers, the analysis is performed separately for the curves and straight segments. In both cases, the unscented Kalman smoother generates better positioning error; 10cm and 23cm improved positioning results in straight segment and curves, respectively.

Autonomous Navigation Algorithm Development with Extended Kalman Filter and Sliding Mode Control (확장형 칼만필터와 슬라이딩 모드 제어기법을 이용한 자율항법 알고리즘 개발)

  • Yun, Duk-Sun;Yu, Hwan-Shin
    • Journal of Advanced Navigation Technology
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    • v.11 no.4
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    • pp.378-387
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    • 2007
  • In this paper, Authors develop and verify the algorithm for enhancing the performance of Unmanned vehicle's Autonomous navigation, and also propose the method of establishing much more precise Navigation locus. Unmanned vehicle has a destination, however orientation is not notified, which make it find the future orientation itself. Extended Kalman Filter make it access to the desirable direction, which coupled with INS and GPS is proposed in this paper. Sliding mode control could overcome the side slip and lateral minor movement of the vehicle. The test result would shows the effectiveness of Extended kalman filter and Slide mode control for the navigation.

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Attitude Determination for Gyroless Spacecraft Using Reaction Wheels (반작용휠을 이용한 자이로 미탑재 위성의 자세결정 기법)

  • Park, Seong-Yong;Kim, Young-Ouk;Leeghim, Henzeh
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.44 no.10
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    • pp.853-861
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    • 2016
  • This paper deals with a new technique utilizing the angular speed of the reaction wheels to determine attitudes and angular rates for gyroless satellites. The suggested algorithm in this study is designed to determine the precise attitude and angular rates under actual space environments by the support of the angular speeds of reaction wheels based on the extended Kalman filter. Furthermore, the proposed approach is also designed to estimate not only the attitude and angular rates of spacecraft but the external disturbances. The numerical simulation was conducted for gyloless spacecraft installed with four reaction wheels of the pyramid-type configuration. The performance of the proposed algorithm is verified by using numerical simulations.

Fault Diagnosis Scheme for Open-Phase Fault of Permanent Magnet Synchronous Motor Drive using Extended Kalman Filter (영구자석 동기전동기 드라이브의 확장형 칼만필터를 이용한 개방성 고장진단 기법)

  • Ahn, Sung-Guk;Park, Byoung-Gun;Kim, Rae-Young;Hyun, Dong-Seok
    • The Transactions of the Korean Institute of Power Electronics
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    • v.16 no.2
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    • pp.191-198
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    • 2011
  • In this paper, the fault diagnosis scheme for PMSM drives has been proposed to maintain control performance under a switch open-phase fault of inverter. When the open-phase fault occurs, the stator resistances of PMSM are estimated by Extended Kalman Filter (EKF) in real time and can appear differently according to the location of fault occurrence to check the fault detection and identification. The control algorithm is configured without the additional device and low cost by adding the existing control program. Also, by using motor parameter the estimated stator resistance value improves the control performance of the controller affected by parameter variation. The feasibility of the proposed fault diagnosis algorithm is validated in simulation and experiment.

Terrain Aided Inertial Navigation for Precise Planetary Landing (정밀 행성 착륙을 위한 지형 보조 관성 항법 연구)

  • Jeong, Bo-Young;Choi, Yoon-Hyuk;Jo, Su-Jang;Bang, Hyo-Choong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.7
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    • pp.673-683
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    • 2010
  • This study investigates Terrain Aided Inertial Navigation(TAIN) which consists of Inertial Navigation System (INS) with the optical sensor for precise planetary landing. Image processing is conducted to extract the feature points between measured terrain data and on-board implemented terrain information. The navigation algorithm with Iterated Extended Kalman Filter(IEKF) can compensate for the navigation error, and provide precise navigation information compared to single INS. Simulation results are used to demonstrate the feasibility of integration to accomplish precise planetary landing. The proposed navigation approach can be implemented to the whole system coupled with guidance and control laws.

Design of GPS-aided Dead Reckoning Algorithm of AUV using Extended Kalman Filter (확장칼만필터를 이용한 무인잠수정의 GPS 보조 추측항법 알고리즘 설계)

  • Kang, Hyeon-Seok;Hong, Sung-Min;Sur, Joo-No;Kim, Joon-Young
    • Journal of Ocean Engineering and Technology
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    • v.31 no.1
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    • pp.28-35
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    • 2017
  • This paper introduces a GPS-aided dead reckoning algorithm that asymptotically estimates the heading bias error of a magnetic compass based on geodetic north, improves the position error accumulated by dead reckoning, and helps the estimated position of an AUV to represent a position in the NED coordinate system, by receiving GPS position information when surfaced. Based on the results of a simulation, the locational error was bounded with a modest distance, after estimating the AUV position and heading bias error of the magnetic compass when surfaced. In other words, it was verified that proposed algorithm improves the position error in the NED coordinate system.

Development of GPS-RTK Algorithm for Improving Geodetic Performance in Short Baseline (단기선 측지 성능 향상을 위한 GPS-RTK 알고리즘 개발)

  • Choi, Byung-Kyu;Lee, Sang-Jeong;Park, Jong-Uk;Baek, Jeong-Ho
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.4
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    • pp.461-467
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    • 2009
  • Relative positioning technique by GPS that can obtain the high positioning accuracy has been used for generation of high precision positioning with elimination or the reduction of the common errors. This paper gives some algorithms for RTK and considers the filter to estimate the positioning information and integer ambiguities at each epoch in the whole algorithms. The extended kalman filter has been employed to estimate the state parameters and the modified LAMBDA to resolve the integer ambiguities. The data processing was performed by GPS single frequency and dual frequency in short baseline. The verification procedure of these positioning compared with results from Bernese 5.0 software. We presented some statistic values on positioning errors and the rates of integer ambiguity resolution.