Title :
State estimation method for aircraft identification purposes
Author_Institution :
Dept. of Control Eng. & Inf. Technol., Budapest Univ. of Technol. & Econ., Budapest, Hungary
Abstract :
The study presents a state estimation method for the determination of an aircraft´s position, speed, spatial orientation and angular velocity based on the data fusion of differential GPS, 3D accelerometer, angular velocity and magnetometer sensors and Extended Kalman Filtering on actual flight data. The paper also proposes a method for determining the aircraft´s angle of attack and sideslip angles. The state variables together with the aircraft´s actuator signals (determined separately) are considered as input signals for the identification of an aircraft´s nonlinear model.
Keywords :
Global Positioning System; Kalman filters; accelerometers; actuators; aircraft control; aircraft instrumentation; angular velocity measurement; magnetic sensors; magnetometers; nonlinear dynamical systems; nonlinear filters; position measurement; sensor fusion; state estimation; 3D accelerometer; aircraft actuator signals; aircraft angle of attack; aircraft nonlinear model identification; aircraft position; angular velocity sensors; data fusion; differential GPS; extended Kalman filtering; magnetometer sensors; sideslip angles; spatial orientation; state estimation method; Acceleration; Aircraft; Aircraft navigation; Aircraft propulsion; Angular velocity; Global Positioning System; State estimation; Aircraft identification; Angle of attack; Data fusion; Extended Kalman filtering; Sideslip angle; State estimation;
Conference_Titel :
Applied Computational Intelligence and Informatics (SACI), 2014 IEEE 9th International Symposium on
Conference_Location :
Timisoara
DOI :
10.1109/SACI.2014.6840090