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

Swee Ho Tang; Takaaki Kojima; Toru Namerikawa; Che Fai Yeong; Eileen Lee Ming Su

doi:10.1109/SICE.2015.7285427

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

Swee Ho Tang, Takaaki Kojima, Toru Namerikawa, Che Fai Yeong, Eileen Lee Ming Su

Department of System Design Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

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.

Original language	English
Title of host publication	2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	695-700
Number of pages	6
ISBN (Print)	9784907764487
DOIs	https://doi.org/10.1109/SICE.2015.7285427
Publication status	Published - 2015 Sep 30
Event	54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015 - Hangzhou, China Duration: 2015 Jul 28 → 2015 Jul 30

Other

Other	54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015
Country	China
City	Hangzhou
Period	15/7/28 → 15/7/30

Keywords

EKF
Position Estimation
UAV
UKF

ASJC Scopus subject areas

Control and Systems Engineering

Access to Document

10.1109/SICE.2015.7285427

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Tang, S. H., Kojima, T., Namerikawa, T., Yeong, C. F., & Su, E. L. M. (2015). Unscented Kalman filter for position estimation of UAV by using image information. In 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015 (pp. 695-700). [7285427] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SICE.2015.7285427

Unscented Kalman filter for position estimation of UAV by using image information. / Tang, Swee Ho; Kojima, Takaaki; Namerikawa, Toru; Yeong, Che Fai; Su, Eileen Lee Ming.

2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 695-700 7285427.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tang, SH, Kojima, T, Namerikawa, T, Yeong, CF & Su, ELM 2015, Unscented Kalman filter for position estimation of UAV by using image information. in 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015., 7285427, Institute of Electrical and Electronics Engineers Inc., pp. 695-700, 54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015, Hangzhou, China, 15/7/28. https://doi.org/10.1109/SICE.2015.7285427

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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.",

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AB - 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.

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

Abstract

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Keywords

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