• 제목/요약/키워드: Target Position Estimation

검색결과 136건 처리시간 0.026초

신경 회로망을 이용한 이동물체의 실시간 위치측정에 대한 연구 (A study on the real-time Position measurements of mobile object using neural network)

  • 노재희;이운근;노영식
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 B
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    • pp.832-834
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    • 1999
  • This paper is a study on the real-position measurements of mobile object using n network. 2-D PSD sensor is used to measure th position of moving object with light source. Position Sensitive Detector(PSD) is an useful which can be used to measure the position o incidence light in accuracy and in real-time. T the position of light source of moving target, neural network technique are proposed and applied. Real-time position measurements of the mobile robot with light source is examined to validate the proposed method. It is shown that the proposed technique provides accurate position estimation of the moving object.

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정합-표적모델 역산을 이용한 기동 표적의 위치 추정 (Matched-target Model Inversion for the Position Estimation of Moving Targets)

  • 장덕홍;박홍배;김성일;류존하;김광태
    • 한국음향학회지
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    • 제22권7호
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    • pp.562-572
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    • 2003
  • 수동 소나를 이용하여 기동 표적의 위치를 추정하는 정합-표적모델 역산 기법을 개발하였다. 본 기법은 수중음향학 분야에서 널리 사용되는 정합장 역산 방법을 이용하여 관측으로부터 얻어지는 방위와 주파수를 표적모델에 의해 계산되는 값과 정합 시킴으로써 표적의 위치를 파악한다. 효율성과 정확성을 향상시키기 위하여 변수의 탐색 방식은 혼성 최적화 기법을 이용하였는데 일차적으로 광역 최적화 기법으로 알려진 유전자 기법이나 모사 담금질 기법을 적용한 후 단순 비탈 국부최적화 기법을 순차적으로 적용하였다. 제안 기법의 성능 검증을 위하여 3가지의 기동 시나리오에 대하여 시뮬레이션을 실시하였다. 검증 결과 가우시안 확률분포를 갖는 측정오차가 5σ를 가지는 경우에도 견실한 수렴을 보여주었으며 계산 시간면에서도 실용적 인 것으로 밝혀졌다.

빈피킹을 위한 스테레오 비전 기반의 제품 라벨의 3차원 자세 추정 (Stereo Vision-Based 3D Pose Estimation of Product Labels for Bin Picking)

  • 우다야 위제나야카;최성인;박순용
    • 제어로봇시스템학회논문지
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    • 제22권1호
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    • pp.8-16
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    • 2016
  • In the field of computer vision and robotics, bin picking is an important application area in which object pose estimation is necessary. Different approaches, such as 2D feature tracking and 3D surface reconstruction, have been introduced to estimate the object pose accurately. We propose a new approach where we can use both 2D image features and 3D surface information to identify the target object and estimate its pose accurately. First, we introduce a label detection technique using Maximally Stable Extremal Regions (MSERs) where the label detection results are used to identify the target objects separately. Then, the 2D image features on the detected label areas are utilized to generate 3D surface information. Finally, we calculate the 3D position and the orientation of the target objects using the information of the 3D surface.

유전자 알고리즘 기반의 수동측거소나 부배열 위치오차 추정 (Position error estimation of sub-array in passive ranging sonar based on a genetic algorithm)

  • 엄민정;김도영;박규태;신기철;오세현
    • 한국음향학회지
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    • 제38권6호
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    • pp.630-636
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    • 2019
  • 수동측거소나는 잠수함 플랫폼의 좌/우현에 각각 3개의 부배열로 구성된 수동소나의 한 종류로서 표적을 탐지하고 방위와 거리를 산출하는 특성을 갖는다. 방위와 거리 산출에는 물리적인 부배열 위치로 인하여 발생되는 시간지연과 삼각측량 기법이 활용된다. 이러한 기법에는 부배열의 정확한 위치정보가 요구되며 부배열의 위치정보가 부정확할 경우 방위와 거리정확도 성능이 저하되는 한계가 있다. 특히 하나의 시간지연을 사용하는 방위보다 두 개의 시간지연 값을 사용하는 거리 정확도 성능에 미치는 영향이 더 크다. 이를 개선하기 위하여 부배열의 위치 오차 추정 및 오차보상에 대한 연구가 필요하다. 본 논문에서는 최적화 탐색 기법인 유전자 알고리즘을 바탕으로 부배열 위치오차를 추정하며, 위치오차로 인한 시간지연 오차 값을 보상하여 거리정확도 성능 개선 방법을 제시하고자 한다. 또한 해상시험 데이터를 이용하여 제시한 알고리즘과 성능을 검증하고자 한다.

A Study on the GPS Error Compensation using Estimation Point of Moving Position at a Vehicle

  • Song, Suck-Woo;Song, Hyun-Sung;Jang, Hong-Seok;Rho, Do-Hwan
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.64.5-64
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    • 2001
  • It is a very important problem that we grasp the accurate position at car navigation system. The GPS has used for knowing position because of accumulating few errors, but it have errors that are Tropospheric error, ionospheric error and Multipath error and so on. In this paper, We estimate moving position of a vehicle by Kalman filter using initial value after deducing the line equation using initial value and target value of map data. Then, we compensate GPS errors compare estimated poing with GPS errors. The experimental results have shown that are compared position data during real travel with compensated position data which are got after applying the algorithm ...

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스마트폰과 Double-Stacked 파티클 필터를 이용한 실외 보행자 위치 추정 정확도 개선에 관한 연구 (A Study on Enhancing Outdoor Pedestrian Positioning Accuracy Using Smartphone and Double-Stacked Particle Filter)

  • 성광제
    • 반도체디스플레이기술학회지
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    • 제22권2호
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    • pp.112-119
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    • 2023
  • In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

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A Study of Optimization of α-β-γ-η Filter for Tracking a High Dynamic Target

  • Pan, Bao-Feng;Njonjo, Anne Wanjiru;Jeong, Tae-Gweon
    • 한국항해항만학회지
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    • 제41권5호
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    • pp.297-302
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    • 2017
  • The tracking filter plays a key role in accurate estimation and prediction of maneuvering the vessel's position and velocity. Different methods are used for tracking. However, the most commonly used method is the Kalman filter and its modifications. The ${\alpha}-{\beta}-{\gamma}$ filter is one of the special cases of the general solution provided by the Kalman filter. It is a third order filter that computes the smoothed estimates of position, velocity, and acceleration for the nth observation, and predicts the next position and velocity. Although found to track a maneuvering target with good accuracy than the constant velocity ${\alpha}-{\beta}$ filter, the ${\alpha}-{\beta}-{\gamma}$ filter does not perform impressively under high maneuvers, such as when the target is undergoing changing accelerations. This study aims to track a highly maneuvering target experiencing jerky motions due to changing accelerations. The ${\alpha}-{\beta}-{\gamma}$ filter is extended to include the fourth state that is, constant jerk to correct the sudden change of acceleration to improve the filter's performance. Results obtained from simulations of the input model of the target dynamics under consideration indicate an improvement in performance of the jerky model, ${\alpha}-{\beta}-{\gamma}-{\eta}$ algorithm as compared to the constant acceleration model, ${\alpha}-{\beta}-{\gamma}$ in terms of error reduction and stability of the filter during target maneuver.

A Study on Optimization of Fourth-Order Fading Memory Filter under the Highly Dynamic Motion of Both Own Ship and Target

  • Pan, Bao-Feng;Jeong, Tae-Gweon
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2017년도 추계학술대회
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    • pp.145-147
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    • 2017
  • Tracking filter plays a key role in accurate estimation and prediction of maneuvering vessel's dynamics. The third-order ${\alpha}-{\beta}-{\gamma}$ filter is one of the special cases of the general solution provided by the Kalman filter. Fading memory algorithm performs a better performance in numerous of ${\alpha}-{\beta}-{\gamma}$ filter algorithms. This study aims to optimize the fourth-order fading memory algorithm ${\alpha}-{\beta}-{\gamma}-{\eta}$ filter, which is extended form ${\alpha}-{\beta}-{\gamma}$ filter, to get much more accurate position of high dynamic target on the condition that the own ship is also high dynamic.

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측정각 Bias 보상을 통한 수동소나체계의 표적기동분석 성능 향상 연구 (Improvement of Target Motion Analysis for a Passive Sonar System with Measurement Bias Estimation)

  • 유필훈;송택렬
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 D
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    • pp.2011-2013
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    • 2001
  • In this paper the MMAE(Multiple Model Adaptive Estimation) algorithm using the MGEKF(Modified Gain Extended Kalman Filter) of which modes are set to be measurement biases is proposed to enhance the performance of target tracking with bearing only measurements. The state are composed of relative position, relative velocity and taregt acceleration. The mode probability is calculated from the bearing only measurements from the HMS(Hull-Mounted Sonar). The proposed algorithm is tested in a series of computer simulation runs.

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이동물체의 추적을 위한 정밀 위치추정 (Precision Position Estimation for Tracking the Moving Object)

  • 인추식;이자성;홍석교;고영길
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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    • pp.335-337
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    • 1994
  • The correlation tracker developed by John M. Fitts in 1979 is the most complex to mechanize but provides the best tracking performance in a low SNR condition. Correlation tracker would rewove the requirements for optimizing threshold and has no need to know information about the target. But if the displacement of the target is large, the tracking error of the correlation tracker tends to diverge. In this paper, we suggest a precision image tracking algorithm which improves the tracking performance via iterative application of the matched filter estimation algorithm.

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