In this paper, a research on Ultra-wideband and Inertial Measurement Unit pose estimation is conducted to track the motion of an Unmanned Aerial Vehicle. Two models have been developed to determine the pose of the target. Using data provided by Ultra-wideband and Inertial Measurement Unit, an Extended Kalman Filter algorithm is adopted to filter noise and obtain precise state of the target after sensor fusion. Simulations of two models show robust and continuous tracking of the Unmanned Aerial Vehicle. The pose estimation performance of simulations is evaluated by mean error and standard deviation. Compared with existing pose estimation methods, the proposed methods are very effective for the reason that they provide all six pose of the target and base stations of Ultra-wideband system can be set up arbitrarily. The proposed methods are suitable for indoor scenarios and some small-area outdoor applications. The main contribution of this paper is two solutions to determine the full six degree of freedom pose of the target.
An initial research on Ultra-wideband and Inertial Measurement Unit pose estimation for Unmanned Aerial Vehicle
2016-08-01
185215 byte
Conference paper
Electronic Resource
English
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