Universiti Teknologi Malaysia Institutional Repository

Unscented Kalman filter for position estimation of UAV by using image information

Tang, Swee Ho and Kojima, Takaaki and Namerikawa, Toru and Yeong, Che Fai and Su, Eileen Lee Ming (2015) Unscented Kalman filter for position estimation of UAV by using image information. In: 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), 2015, 28-30 Jul, 2015, China.

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Official URL: http://www.ieee-ras.org/component/rseventspro/even...

Abstract

In this paper, the position estimation problem is solved by using unscented Kalman filter with observation uncertainty’s compensations. These observation uncertainties causing the estimation become inaccurate in position estimate problem. Visual observation is difficult for an unmanned aerial vehicle equipped with only a monocular-vision camera and often results in observation error because of the detected blurred images. A method to weight the observations is proposed in order to improve the position estimation. Simulation is performed using MATLAB and Simulink to verify the proposed method. The simulation result shows that the proposed method can estimate the position accurately.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:UAV, position estimation
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885-7895 Computer engineer. Computer hardware
Divisions:Electrical Engineering
ID Code:61326
Deposited By: Widya Wahid
Deposited On:31 Mar 2017 14:35
Last Modified:22 Aug 2017 14:39

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