• Title/Summary/Keyword: Initial position error

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Outdoor Positioning Estimation of Multi-GPS / INS Integrated System by EKF / UPF Filter Conversion (EKF/UPF필터 변환을 통한 Multi-GPS/INS 융합 시스템의 실외 위치추정)

  • Choi, Seung-Hwan;Kim, Gi-Jeung;Kim, Yun-Ki;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.12
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    • pp.1284-1289
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    • 2014
  • In this Paper, outdoor position estimation system was implemented using GPS (Global Positioning System) and INS (Inertial Navigation System). GPS position information has lots of errors by interference from obstacles and weather, the surrounding environment. To reduce these errors, multiple GPS system is used. Also, the Discrete Wavelet Transforms was applied to INS data for compensation of its error. In this paper, position estimation of the mobile robot in the straight line is conducted by EKF (Extended Kalman Filter). However, curve running position estimation is less accurate than straight line due to phase change in rotation. The curve is recognized through the rate of change in heading angle and the position estimation precision of the initial curve was improved by UPF (Unscented Particle Filter). In the case of UPF, if the number of particle is so many that big memory gets size is needed and processing speed becomes late. So, it only used the position estimation in the initial curve. Thereafter, the position of mobile robot in curve is estimated through switching from UPF to EKF again. Through the experiments, we verify the superiority of the system and make a conclusion.

Stochastic Error Compensation Method for RDOA Based Target Localization in Sensor Network (통계적 오차보상 기법을 이용한 센서 네트워크에서의 RDOA 측정치 기반의 표적측위)

  • Choi, Ga-Hyoung;Ra, Won-Sang;Park, Jin-Bae;Yoon, Tae-Sung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.10
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    • pp.1874-1881
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    • 2010
  • A recursive linear stochastic error compensation algorithm is newly proposed for target localization in sensor network which provides range difference of arrival(RDOA) measurements. Target localization with RDOA is a well-known nonlinear estimation problem. Since it can not solve with a closed-form solution, the numerical methods sensitive to initial guess are often used before. As an alternative solution, a pseudo-linear estimation scheme has been used but the auto-correlation of measurement noise still causes unacceptable estimation errors under low SNR conditions. To overcome these problems, a stochastic error compensation method is applied for the target localization problem under the assumption that a priori stochastic information of RDOA measurement noise is available. Apart from the existing methods, the proposed linear target localization scheme can recursively compute the target position estimate which converges to true position in probability. In addition, it is remarked that the suggested algorithm has a structural reconciliation with the existing one such as linear correction least squares(LCLS) estimator. Through the computer simulations, it is demonstrated that the proposed method shows better performance than the LCLS method and guarantees fast and reliable convergence characteristic compared to the nonlinear method.

Face and Hand Tracking Algorithm for Sign Language Recognition (수화 인식을 위한 얼굴과 손 추적 알고리즘)

  • Park, Ho-Sik;Bae, Cheol-Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.11C
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    • pp.1071-1076
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    • 2006
  • In this paper, we develop face and hand tracking for sign language recognition system. The system is divided into two stages; the initial and tracking stages. In initial stage, we use the skin feature to localize face and hands of signer. The ellipse model on CbCr space is constructed and used to detect skin color. After the skin regions have been segmented, face and hand blobs are defined by using size and facial feature with the assumption that the movement of face is less than that of hands in this signing scenario. In tracking stage, the motion estimation is applied only hand blobs, in which first and second derivative are used to compute the position of prediction of hands. We observed that there are errors in the value of tracking position between two consecutive frames in which velocity has changed abruptly. To improve the tracking performance, our proposed algorithm compensates the error of tracking position by using adaptive search area to re-compute the hand blobs. The experimental results indicate that our proposed method is able to decrease the prediction error up to 96.87% with negligible increase in computational complexity of up to 4%.

Real Time Image Acquisition System using a Image Intensifier and Position Error Verification (영상증배관을 이용한 실시간 영상획득시스템과 위치오차검증)

  • Lee, Dong-Hoon;Kim, Nam-Hoon;Jeong, Jong-Beom
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.11 no.4
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    • pp.331-338
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    • 2017
  • In this study, a portable x-ray generator was manufactured and a real-time image acquisition system was constructed using the image intensifier from the generated generator. We have developed a real - time position error verification system that can verify whether the artificial joint position is different from the initial image from the acquired image. The template image of the region of interest is extracted from the reference image using the pattern matching technique and compared with the image to be compared. As a result, It is shown that real - time position error verification is achieved by displaying the difference angle. This system is portable type, has a self-shielding facility, and the output of the irradiation device can be manufactured in a small size of 1kw and can be used as a portable type. In case of emergency patients in the non-destructive field for industrial use, It has proved effective for use in small areas such as feet.

Measurement Delay Error Compensation for GPS/INS Integrated System (GPS/INS 통합시스템의 측정치 시간지연오차 보상)

  • Lyou Joon;Lim You-Chol
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.41 no.1
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    • pp.1-8
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    • 2004
  • The INS(Inertial Navigation System) provides high rate position, velocity and attitude data with good short-term stability while the GPS(Global Position System) provides position and velocity data with long-term stability. By integrating the INS with GPS, a navigation system can be achieved to Provide highly accurate navigation Performance. For the best performance, time synchronization of GPS and INS data is very important in GPS/INS integrated system But, it is impossible to synchronize them exactly due to the communication and computation time-delay. In this paper, to reduce the error caused by the measurement time-delay in GPS/INS integrated systems, error compensation methods using separate bias Kalman filter are suggested for both the loosely-coupled and the tightly-coupled GPS/INS integration systems. Linearized error models for the position and velocity matching GPS/INS integrated systems are Int derived by linearizing with respect to its time-delay and augmenting the delay-state into the conventional state equations for each case. And then separate bias Kalman Inter is introduced to estimate the time-delay during only initial navigation stage. The simulation results show that the present method is effective enough resulting in considerably less position error.

A Comparative Study of a Variable Overlap-area Type and Conventional Types in the Inductive Precision Position Measurement System (자속경로 단면적 및 공극변화를 이용한 인던턴스형 초정밀 변위측정 시스템)

  • Choe, Dong-Jun;Choe, In-Muk;Kim, Su-Hyeon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.2
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    • pp.254-259
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    • 2002
  • A variable air-gap type system is widely used for inductive precision position measurement systems. This type transducer has high sensitivity but lacks a linear measurement range due to structural nonlinearity. Furthermore, as measurement range increases, linearity error is also increased. The alternative is a variable overlap-area type system. The sensitivity of this type is determined by the initial air-gap dimension, keeps the original value and does not deteriorate linearity in spite of the variations of the measuring range.

Application of GNSS Multipath Map by Correction Projection to Position Domain in Urban Canyon (도심지 GNSS 다중경로 오차 지도 적용을 위한 다중경로 보정정보 위치 영역 투영 기법)

  • Yongjun Lee;Heonho Choi;Byungwoon Park
    • Journal of Advanced Navigation Technology
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    • v.28 no.1
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    • pp.155-158
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    • 2024
  • Multipath, a major error source in urban GNSS positioning (global navigation satellite system), pose a challenge due to its site-dependent nature, varying with the user's signal reception environment. In our previous study, we introduced a technique generating GNSS multipath map in urban canyon. However, due to uncertainty in initial GNSS positions, applying multipath maps required generating multiple candidate positions. In this study, we present an efficient method for applying multipath maps by projecting the multipath correction in position domain. This approach effectively applies multipath maps, addressing the challenges posed by urban user position uncertainties.

Compensation of SDINS Navigation Errors Using Line-Of-Sight Vector (시선벡터를 이용한 관성항법장치의 보정기법)

  • Lim, You-Chol;Yim, Jong-Bin;Lyou, Joon
    • Proceedings of the IEEK Conference
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    • 2003.07c
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    • pp.2521-2524
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    • 2003
  • Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors (accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range missile missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System (SDINS) using Line-Of-Sight(LOS) vector from star sensor. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the bounded-ness of position and attitude errors.

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A New Stylization Method using Least-Square Error Minimization on Segmental Pitch Contour (최소 자승오차 방식을 이용한 세그먼트 피치패턴의 정형화)

  • 이정철
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06c
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    • pp.107-110
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    • 1994
  • In this paper, we describe the features of the fundamental frequency contour of Korean read speech, and propose a new stylization method to characterize the Fø pattern of segments. Our algorithm consists of three stylization processes : the segment level, the syllable level, and the sord level. For stylization of Fø contour in the segment level , we applied least square error minimization method to determine Fø values at initial, medial, and final position in a segment. In the syllable level, we determine the stylized Fø pattern of a syllable using the mean Fø value of each word and style information for each word, syllable and segment, we reconstruct Fø contour of sentences. The simulation results show that the error is less than 10% of the actual Fø contour for each sentence. In perception test, there is little difference between the synthesized speech with the original difference between the synthesized speech with the original Fø contour and the synthesized speech with the stylized Fø contour.

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An Effective Mapping for a Mobile Robot using Error Backpropagation based Sensor Fusion (오류 역전파 신경망 기반의 센서융합을 이용한 이동로봇의 효율적인 지도 작성)

  • Kim, Kyoung-Dong;Qu, Xiao-Chuan;Choi, Kyung-Sik;Lee, Suk-Gyu
    • Journal of the Korean Society for Precision Engineering
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    • v.28 no.9
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    • pp.1040-1047
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    • 2011
  • This paper proposes a novel method based on error back propagation neural networks to fuse laser sensor data and ultrasonic sensor data for enhancing the accuracy of mapping. For navigation of single robot, the robot has to know its initial position and accurate environment information around it. However, due to the inherent properties of sensors, each sensor has its own advantages and drawbacks. In our system, the robot equipped with seven ultrasonic sensors and a laser sensor navigates to map two different corridor environments. The experimental results show the effectiveness of the heterogeneous sensor fusion using an error backpropagation algorithm for mapping.