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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Bibliographic Details
Published inProceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693) Vol. 4; pp. 2360 - 2364 Vol.4
Main Authors Xian-Chun Bi, Jin-Chun Hu, Ji-Hong Zhu, Zeng-Qi Sun
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Bismuth
Degradation
Gaussian noise
Global Positioning System
Helicopters
Least squares approximation
Recursive estimation
Robot kinematics
State estimation
Sun
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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.
ISBN:0780378652
9780780378650
9780780381315
0780381319
DOI:10.1109/ICMLC.2003.1259904