• Title/Summary/Keyword: Moving target

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Target Position Correction Method in Monopulse GMTI Radar (GMTI 표적의 위치 보정 방법)

  • Kim, So-Yeon
    • Korean Journal of Remote Sensing
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    • v.36 no.3
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    • pp.441-448
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    • 2020
  • GMTI (Ground Moving Target Indication) radar system can detect ground moving targets and can provide position and velocity information of each target. However, the azimuth position of target has some offset because of the hardware errors such as mechanical tolerances. In this case, an error occurs no matter how accurate the monopulse ratio is. In this paper, target position correction method in azimuth direction has been proposed. The received sum and difference signals of monopulse GMTI system are post-processed to correct the target azimuth angle error. This method is simple and adaptive for nonhomogeneous area because it can be implemented by using only software without any hardware modification or addition.

Novel velocity detection of moving object with rough surface vertically illuminated by self-mixing laser diode

  • Shibata, Takaaki;Shinohara, Shigenobu;Ikeda, Hiroaki;Yoshida, Hirofumi;Sumi, Masao
    • 제어로봇시스템학회:학술대회논문집
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    • 1994.10a
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    • pp.494-497
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    • 1994
  • We propose a novel velocity detection method of moving object based on a speckle pattern on the target surface using a self-mixing laser diode (SMLD). By this measurement, it was confirmed that the speckle signal has its waveform independent of the target velocity, and has its averaged frequency directly proportional to the target velocity. So it will be possible to detect the velocity of the target transversely translating against the laser light beam using a compact measuring system.

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Design of target state estimator and predictor using multiple model method (다중모델기법을 이용한 표적 상태추정 및 예측기 설계연구)

  • Jung, Sang-Geun;Lee, Sang-Gook;Yoo, Jun
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.478-481
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    • 1996
  • Tracking a target of versatile maneuver recently demands a stable adaptation of tracker, and the multiple model techniques are being developed because of its ability to produce useful information of target maneuver. This paper presents the way to apply the multiple model method in a moving-target and moving-platform scenario, and the estimation and prediction results better than those of single Kalman filter.

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Ground Moving Target Displacement Compensation and Performance Analysis in the DPCA Based SAR-GMTI System (DPCA 기법을 이용한 SAR-GMTI 시스템에서 지상 이동 표적 오차 보상 기법 및 성능 분석)

  • Jung, Jae-Hoon;Jung, Jung-Soo;Jung, Chul-Ho;Kwag, Young-Kil
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.20 no.11
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    • pp.1138-1144
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    • 2009
  • The velocity and acceleration of the ground moving target can cause the target position to be displaced and defocused in the SAR image. In this paper, the displacement compensation scheme is presented to correct the displaced position and defocused moving target image in the DPCA based SAR-GMTI system. The influence of the ground moving target due to the velocity and acceleration is analyzed in range and azimuth directions, and its compensation method is presented with the simulation results. The performance of the proposed method is compared with respect to the estimated velocity and defocused quantity in both range and azimuth directions.

A search mechanism for moving objects in a spatial database (공간 데이타베이스에서 이동 객체의 탐색기법)

  • 유병구;황수찬;백중환
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.1
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    • pp.25-33
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    • 1998
  • This paepr presents an algorithm for searching an object in a fast way which contains a continuous moving object in multi-dimensional spatical databases. This algorithm improves the search method of R-tree for the case that a target object is continuously moving in a spatial database. It starts the searching from the current node instead of the root of R-tree. Thus, the algorithm will find the target object from the entries of current node or sibling nodes in the most cases. The performance analysis shows that it is more efficient than the existing algorithm for R-tree when search windows or target objects are continuously moving.

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Estimation of Person Height and 3D Location using Stereo Tracking System (스테레오 추적 시스템을 이용한 보행자 높이 및 3차원 위치 추정 기법)

  • Ko, Jung Hwan;Ahn, Sung Soo
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.2
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    • pp.95-104
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    • 2012
  • In this paper, an estimation of person height and 3D location of a moving person by using the pan/tilt-embedded stereo tracking system is suggested and implemented. In the proposed system, face coordinates of a target person is detected from the sequential input stereo image pairs by using the YCbCr color model and phase-type correlation methods and then, using this data as well as the geometric information of the stereo tracking system, distance to the target from the stereo camera and 3-dimensional location information of a target person are extracted. Basing on these extracted data the pan/tilt system embedded in the stereo camera is controlled to adaptively track a moving person and as a result, moving trajectory of a target person can be obtained. From some experiments using 780 frames of the sequential stereo image pairs, it is analyzed that standard deviation of the position displacement of the target in the horizontal and vertical directions after tracking is kept to be very low value of 1.5, 0.42 for 780 frames on average, and error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 0.5% on average. These good experimental results suggest a possibility of implementation of a new stereo target tracking system having a high degree of accuracy and a very fast response time with this proposed algorithm.

Moving Target Indication using an Image Sensor for Small UAVs (소형 무인항공기용 영상센서 기반 이동표적표시 기법)

  • Yun, Seung-Gyu;Kang, Seung-Eun;Ko, Sangho
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.12
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    • pp.1189-1195
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    • 2014
  • This paper addresses a Moving Target Indication (MTI) algorithm which can be used for small Unmanned Aerial Vehicles (UAVs) equipped with image sensors. MTI is a system (or an algorithm) which detects moving objects. The principle of the MTI algorithm is to analyze the difference between successive image data. It is difficult to detect moving objects in the images recorded from dynamic cameras attached to moving platforms such as UAVs flying at low altitudes over a variety of terrain, since the acquired images have two motion components: 'camera motion' and 'object motion'. Therefore, the motion of independent objects can be obtained after the camera motion is compensated thoroughly via proper manipulations. In this study, the camera motion effects are removed by using wiener filter-based image registration, one of the non-parametric methods. In addition, an image pyramid structure is adopted to reduce the computational complexity for UAVs. We demonstrate the effectiveness of our method with experimental results on outdoor video sequences.

Effects of target types and retinal eccentricity on visual search (시각탐색에서 표적 유형과 망막 이심율 효과)

  • 신현정;권오영
    • Korean Journal of Cognitive Science
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    • v.14 no.3
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    • pp.1-11
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    • 2003
  • Two experiments were conducted to investigate effects of target types and retinal eccentricity on the search of a target while both target and background stimuli were static or moving. A visual search task was used in both experiments. The retinal eccentricity was determined by five concentric circles increasing by the unit of 1.6 and the target was different from the background stimuli in either orientation(orientation target) or a distinctive feature(feature target). In Experiment 1 where both the target and background stimuli were presented statically, an interaction between retinal eccentricity arid target type was found. While search time of the orientation target was not affected by the retinal eccentricity, that of the feature target increased as the retinal eccentricity increased. In Experiment 2 where all stimuli were moving, the interaction effect was also found. But the reason was not the same as that in Experiment 1. In the moving condition, while the search time of the orientation target decreased consistently as the retinal eccentricity increased, that of the feature target was not affected by the retinal eccentricity. The implications and limitations of the present results were discussed with respects to the real world situations such as driving cars or flying airplanes.

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Recognizing Static Target in Video Frames Taken from Moving Platform

  • Wang, Xin;Sugisaka, Masanori;Xu, Wenli
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.673-676
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    • 2003
  • This paper deals with the problem of moving object detection and location in computer vision. We describe a new object-dependent motion analysis method for tracking target in an image sequence taken from a moving platform. We tackle these tasks with three steps. First, we make an active contour model of a target in order to build some of low-energy points, which are called kernels. Then we detect interest points in two windows called tracking windows around a kernel respectively. At the third step, we decide the correspondence of those detected interest points between tracking windows by the probabilistic relaxation method In this algorithm, the detecting process is iterative and begins with the detection of all potential correspondence pair in consecutive image. Each pair of corresponding points is then iteratively recomputed to get a globally optimum set of pairwise correspondences.

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A Moving Target Tracking Algorithm Using Integral Projection (가산 투엽법을 이용한 이동 물체 추적 방법)

  • 김태원;서일홍;양해원;오상록;임달호
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.38 no.7
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    • pp.569-581
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    • 1989
  • This paper deals with a tracking algorithm based on integral projection which tracks moving targets with varying brightness and size. An adaptive windowing technique is employed to reduce the sensitivity of the system to the complex background image and also to reduce the computational load. The threshold value is determined by considering both the size and the threshold value of the brightness intensity of the recognized target obtained in the previous processing step. Window position is estimated by using the information of the velocity and acceleration of the target. And integral projection is applied to find the position of the target in the window accurately. Experimental results show that moving targets with varying brightness and size can be tracked properly in noisy environments.

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