State Estimation of a Nonlinear Unmanned Aerial Vehicle Model using an Extended Kalman Filter

An Extended Kalman Filter is designed in order to estimate both state variables and wind velocity vector at the same time for a non conventional unmanned aircraft. The proposed observer uses few measurements, obtained by means of either conventional simple air data sensors or a low cost GPS. To cope with the low rate of the GPS with respect to the other sensors, the EKF algorithm has been modified to allow for a dual rate measurement model. State propagation is obtained by means of an accurate six degrees of freedom nonlinear model of the aircraft dynamics. To obtain joint estimation of state and disturbance, wind velocity components are included in the set of the state variables. Both stoc…

Estimation of turbulence and state based on EKF for a tandem Canard UAV

This paper deals with the state and turbulence estimation of a model describing the longitudinal dynamics of an Unmanned Aerial Vehicle (UAV). Due to both the high nonlinearities of the model and the stochastic nature of disturbances, an Extended Kalman Filter (EKF) is proposed. To allow the estimator to be employed on low cost UAV systems, it is assumed that the aircraft is equipped with a low performance GPS, characterized by a relatively low refresh rate. The designed EKF is able to work efficiently in both turbulent and calm atmosphere. In order to obtain information about the performances of the proposed estimator for control purposes, a control system, consisting of the EKF, a PID-typ…

A NON CONVENTIONAL UAV IN GROUND EFFECT: ESTIMATION OF STATE AND TURBULENCE VIA EXTENDED KALMAN FILTER

ABSTRACT This paper discusses the synthesis of an Extended Kalman Filter (EKF) to perform both wind velocities and state estimation for a non conventional UAV flying in ground effect. Since, in IGE flight, motions into the symmetry plane are of primary concern, the study focuses on the longitudinal aircraft dynamics. The proposed estimator requires measurement of few flight variables, easily obtainable by means of conventional sensors; besides, it does not use Inertial Measurement Unit (IMU). To simulate a low cost sensing equipment, the model outputs are corrupted by white noise of relatively high standard deviation. Furthermore, to cope with the low rate of the GPS with respect to the oth…

Turbolence and State Estimation Via Extended Kalman Filter for a Non Conventional UAV

Collision Avoidance Problem for an Ekranoplan

A Feasibility Analysis For Wig’s As A Civil Transport System In The Mediterranean Sea

State Estimation of a Nonlinear Unmanned Aerial Vehicle Model using an Extended Kalman Filter