• Title/Summary/Keyword: Moving target tracking

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Cooperative Control of Multiple Unmanned Aircraft for Standoff Tracking of a Moving Target (지상 목표물 추적을 위한 다수 무인항공기의 협력제어)

  • Yoon, Seung-Ho;Kim, You-Dan
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.39 no.2
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    • pp.114-120
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    • 2011
  • This paper presents a cooperative standoff tracking of a moving target using multiple unmanned aircraft. To provide guidance commands, vector fields are designed utilizing the Lyapunov stability theory. A roll angle command is generated to keep a constant distance from the target in a circular motion. A speed command and a heading angle command are designed to keep a constant phase angle with respect to the front aircraft and to prevent a collision between aircraft. Numerical simulation is performed to verify the tracking and collision performance of the proposed control laws.

A Fast Moving Object Tracking Method by the Combination of Covariance Matrix and Kalman Filter Algorithm (공분산 행렬과 칼만 필터를 결합한 고속 이동 물체 추적 방법)

  • Lee, Geum-boon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.6
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    • pp.1477-1484
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    • 2015
  • This paper proposes a robust method for object tracking based on Kalman filters algorithm and covariance matrix. As a feature of the object to be tracked, covariance matrix ensures the continuity of the moving target tracking in the image frames because the covariance is addressed spatial and statistical properties as well as the correlation properties of the features, despite the changes of the form and shape of the target. However, if object moves faster than operation time, real time tracking is difficult. In order to solve the problem, Kalman filters are used to estimate the area of the moving object and covariance matrices as a feature vector are compared with candidate regions within the estimated Kalman window. The results show that the tracking rate of 96.3% achieved using the proposed method.

VTG based Moving Target Tracking Performance Improvement Method using MITL System in a Maritime Environment (해상환경에서 MITL 시스템을 활용한 VTG 기반 기동표적 추적성능 개선 기법)

  • Baek, Inhye;Woo, S.H. Arman
    • Journal of Korea Multimedia Society
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    • v.22 no.3
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    • pp.357-365
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    • 2019
  • In this paper, we suggest the tracking method of moving multi-objects in maritime environments. The image acquisition is conducted using IR(InfraRed) camera sensors on an airborne platform. Under the circumstance of maritime, the qualities of IR images can be significantly degraded due to the clutter influence, which directly gives rise to a tracking loss problem. In order to reduce the effects from the clutters, we introduce a technical approach under Man-In-The-Loop(MITL) system for enhancing the tracking performance. To demonstrate the robustness of the proposed approach based on VTG(Valid Tracking Gate), the simulations are conducted utilizing the airborne IR video sequences: Then, the tracking performances are compared with the existing Kalman Filter tracking techniques.

Implementation of Moving Object Recognition based on Deep Learning (딥러닝을 통한 움직이는 객체 검출 알고리즘 구현)

  • Lee, YuKyong;Lee, Yong-Hwan
    • Journal of the Semiconductor & Display Technology
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    • v.17 no.2
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    • pp.67-70
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    • 2018
  • Object detection and tracking is an exciting and interesting research area in the field of computer vision, and its technologies have been widely used in various application systems such as surveillance, military, and augmented reality. This paper proposes and implements a novel and more robust object recognition and tracking system to localize and track multiple objects from input images, which estimates target state using the likelihoods obtained from multiple CNNs. As the experimental result, the proposed algorithm is effective to handle multi-modal target appearances and other exceptions.

Implementation of Tracking and Capturing a Moving Object using a Mobile Robot

  • Kim Sang-joo;Park Jin-woo;Lee Jang-Myung
    • International Journal of Control, Automation, and Systems
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    • v.3 no.3
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    • pp.444-452
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    • 2005
  • A new scheme for a mobile robot to track and capture a moving object using camera images is proposed. The moving object is assumed to be a point-object and is projected onto an image plane to form a geometrical constraint equation that provides the position data of the object based on the kinematics of the active camera. Uncertainties in position estimation caused by the point-object assumption are compensated for using the Kalman filter. To generate the shortest time path to capture the moving object, the linear and angular velocities are estimated and utilized. In this paper, the experimental results of the tracking and capturing of a target object with the mobile robot are presented.

A performance improvement method in the gun fire control system compensating for measurement bias error of the target tracking sensor (표적추적센서의 측정 바이어스 오차 보상에 의한 사격통제장치 성능 향상 기법)

  • Kim, Jae-Hun;Lyou, Joon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.3 no.2
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    • pp.121-130
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    • 2000
  • A practical method is proposed to improve hit probability of the digital gun fire control system, when the measured rate of the tracking sensor becomes biased under some operational situation. For ground moving target it is shown that the well-known Kalman filter which uses position measurement only can be optimally used to eliminate the rate bias error. On the other hand, for 3D moving aircraft we present a new algorithm which incorporate FIR-type filter, which uses position and rate measurement at the same time, and the fixed-lag smoother using position measurement only, and show that it has the optimal performance in terms of both estimation accuracy and response time.

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Tracking of Moving Object using Fuzzy Prediction (퍼지 예측을 이용한 이동물체 추적)

  • Lim, Yong-Ho;Baek, Joong-Hwan;Hwang, Soo-Chan
    • Journal of Advanced Navigation Technology
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    • v.5 no.1
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    • pp.26-36
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    • 2001
  • One of the most important problems in time-varying image sequences is the automatic target tracking. This paper proposes a position prediction and tracking technique of moving object using fuzzy prediction. First, the object is segmented from background of the image using accumulative difference image technique. Then centroid of the segmented object is extracted by using the centroid method, and we propose to apply variable size searching window to the object in order to increase the tracking performance. Also, non-linear prediction is required for efficient object tracking. Therefore, in this paper, fuzzy prediction method is proposed for predicting the location of the moving object at next frame. An experimental result shows that the proposed fuzzy prediction system tracks the moving object in stable under various conditions.

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Development of Cooperative Object Tracking Algorithm Under the Sensor Network Environment (센서네트워크 상황하의 협력적 물체 추적 알고리즘 개발)

  • Kim, Sung-Ho;Kim, Si-Hwan
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.6
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    • pp.710-715
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    • 2006
  • With recent advances in device fabrication technology, economical deployment of large scale sensor networks, a design of pervasive monitoring and control system has been made possible. In this paper, we present a new algorithm for one of the most likely applications for sensor networks; tracking moving targets. The proposed algorithm uses a cooperations between the sensor nodes which detect moving objects. Therefore, the proposed scheme is robust against prediction failures which may result in temporary loss of the target. Using simulations we show that tile proposed moving object tracking algorithm is capable of accurately tracking targets with random movement patterns.