Position estimation for autonomous flight of unmanned helicopter based on low-cost dual GPS
A novel technique to estimate the position of an unmanned helicopter using dual GPS units is presented in this paper. Our approach is to use recursive least square (RLS) method to estimate the noise characteristics with AR(2) model, and adopt Kalman filter to estimate the helicopter position under A...
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Published in | Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693) Vol. 4; pp. 2360 - 2364 Vol.4 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
2003
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Subjects | |
Online Access | Get full text |
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Summary: | A novel technique to estimate the position of an unmanned helicopter using dual GPS units is presented in this paper. Our approach is to use recursive least square (RLS) method to estimate the noise characteristics with AR(2) model, and adopt Kalman filter to estimate the helicopter position under AR(2) noise model. The uniqueness of our attempt lies in using inexpensive commercial GPS units. Simulation results of the estimation system show its effect. |
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ISBN: | 0780378652 9780780378650 9780780381315 0780381319 |
DOI: | 10.1109/ICMLC.2003.1259904 |