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�������պ����ѧѧ�� 2006, Vol. 32 Issue (11) :1349-1353    DOI:
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1. �������պ����ѧ ������ѧ���繤��ѧԺ, ���� 100083;
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Visual 3D motion estimation of UAV and landing target based on extended Kalman filter
Wang Rui, Yan Peng, Liu Hongying, Zhang Guangjun*
1. School of Instrument Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China;
2. School of Science, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

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Abstract�� During the last phase of auto landing an UAV (unmanned aerial vehicle) on the ship, the estimation of the 3D relative motion parameters between UAV and the landing target can be regarded as the planar 3D motion estimation between the camera mounted on the UAV and the deck. An algorithm for visual motion estimation of 3D objects based on extended Kalman filter is presented. First, the camera coordinate with the origin at the camera′s lens and the world coordinate are set up appealing to the principles of perspective projection. Then, the actual 3D camera motion parameters (the three Eulerian angles, transition vectors and their velocities) can be described in terms of the state equation. Furthermore, with the target corner extraction and frame matching, the observation equation is proposed to give the relationship of the feature points in the image and the state vectors. All the 3D relative motion parameters are solved by the stated EKF(extended Kalman filter) method. The presented experimental results of both synthetic data and the real image sequences show that our algorithm is effectively and robust.
Keywords�� 3D motion estimation   extended Kalman filter(EKF)   image sequences   unmanned aerial vehicles (UAV)   vision guide     
Received 2006-04-30;
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About author: �� �(1965-),Ů,������,������,wangr@buaa.edu.cn.
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���, ����, ����Ӣ, �Ź��.������չ�������˲��Ľ������λ�˹���[J]  �������պ����ѧѧ��, 2006,V32(11): 1349-1353
Wang Rui, Yan Peng, Liu Hongying, Zhang Guangjun.Visual 3D motion estimation of UAV and landing target based on extended Kalman filter[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2006,V32(11): 1349-1353
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