Target state estimation for vision-based landing on a moving ground target

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This paper describes vision-based target state estimation approaches for autonomous landing on a moving ground target. The state of moving ground target is estimated by using vision information from a gimbaled camera on an Unmanned Aerial Vehicle (UAV). Using the information from vision system, the UAV estimates the state of a moving target on the ground using the Unscented Kalman Filter (UKF). In this paper, three types of process model are compared by numerical simulations: state in inertial frame, state in inertial frame with position uncertainty of UAV, and relative state with acceleration of UAV.
Publisher
Institute of Electrical and Electronics Engineers Inc.
Issue Date
2016-06
Language
English
Citation

2016 International Conference on Unmanned Aircraft Systems, ICUAS 2016, pp.657 - 663

ISSN
2373-6720
DOI
10.1109/ICUAS.2016.7502552
URI
http://hdl.handle.net/10203/313220
Appears in Collection
AE-Conference Papers(학술회의논문)
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