@inproceedings{9cc47b92e84d4f3088808fb74952f2ff,
title = "Maneuvering target tracking and motion estimation using vision-aid particle filter",
abstract = "The purpose of this paper is to solve the problem of tracking a maneuvering ground moving target (GMT) in the presence of unknown control inputs by an unmanned aerial vehicle (UAV) equipped with a single vision camera. When the exact state information of the GMT is available, the efficiency of the Lyapunov guidance vector field approach has been proved. However, the case of unknown inputs and unavailable state information is still in suspense. By combining the guidance law with a vision-aid particle filter, we propose an integrated tracking algorithm. The guidance law could generate the desired velocity to direct the UAV to loiter around the GMT with a desired radius and airspeed, and the particle filter is capable to estimate the unknown inputs and further estimate the position and velocity of the GMT. The performance of the proposed tracking algorithm is demonstrated through computer simulations.",
keywords = "Lyapunov guidance vector, UAV, loitering control, maneuvering target tracking, particle filter",
author = "Fei Dong and Jiaqi Zhang and Keyou You",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 ; Conference date: 29-10-2017 Through 01-11-2017",
year = "2017",
month = dec,
day = "15",
doi = "10.1109/IECON.2017.8217176",
language = "英语",
series = "Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6733--6738",
booktitle = "Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society",
address = "美国",
}