Title :
Position estimation for autonomous flight of unmanned helicopter based on low-cost dual GPS
Author :
Bi, Xian-chun ; Jin-Chun Hu ; Zhu, Ji-hong ; Sun, Zengqi
Author_Institution :
State Key Lab. of Intelligent Technol. & Syst., Tsinghua Univ., Beijing, China
Abstract :
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.
Keywords :
Global Positioning System; Kalman filters; aircraft control; helicopters; least mean squares methods; position control; recursive estimation; remotely operated vehicles; Kalman filter; autonomous flight; low-cost dual GPS; position estimation; recursive least square method; unmanned helicopter; Bismuth; Degradation; Gaussian noise; Global Positioning System; Helicopters; Least squares approximation; Recursive estimation; Robot kinematics; State estimation; Sun;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259904
