Airspeed estimation of aircraft using two different models and nonlinear observers

Abstract: When operating an aircraft, inaccurate measurements can have devastating consequences. For example, when measuring airspeed using a pitot tube, icing effects and other faults can result in erroneous measurements. Therefore, this master thesis aims to create an alternative method which utilizes known flight mechanical equations and sensor fusion to create an estimate of the airspeed during flight. For validation and generation of flight data, a simulation model developed by SAAB AB, called ARES, is used.  Two models are used to describe the aircraft behavior. One of which is called the dynamic model and utilizes forces acting upon the aircraft body in the equations of motion. The other model, called the kinematic model, instead describes the motion with accelerations of the aircraft body. The measurements used are the angle of attack (AoA), side-slip angle (SSA), GPS velocities, and angular rates from an inertial measurement unit (IMU). The dynamic model assumes that engine thrust and aerodynamic coefficients are already estimated to calculate resulting forces, meanwhile the kinematic model instead uses body fixed accelerations from the IMU. These models are combined with filters to create estimations of the airspeed. The filters used are the extended Kalman filter (EKF) and unscented Kalman filter (UKF). These are combined with the two models to create in total four methods to estimate the airspeed.  The results show no major difference in the performance between the filters except for computational time, for which the EKF has the fastest. Further, the result show similar airspeed estimation performance between the models, but differences can be seen. The kinematic model manages to estimate the wind with higher details and to converge faster, compared to the dynamic model. Both models suffer from an observability problem. This problem entails that the aircraft needs to be maneuvered to excite the AoA and SSA in order for the estimation methods to evaluate the wind, which is crucial for accurate airspeed estimation. The robustness of the dynamic model regarding errors in engine thrust and aerodynamic coefficients are also researched, which shows that the model is quite robust against errors in these values.