Frenet-Based Algorithm for Trajectory Prediction

Abstract

An algorithm for aircraft trajectory prediction is presented, that is based on a third-order accurate algebraic expansion of the aircraft center of gravity (e.g.) trajectory in the Frenet frame. This technique allows for an efficient evaluation of future e.g. positions in a time interval the extension of which depends on the aircraft maneuver state. The evaluation of the coefficients in the series expansion requires the knowledge of aircraft e.g. acceleration and its time derivative. Estimates of first and second derivatives of rate-gyro signals are also necessary when the accelerometers are not located in the aircraft e.g. A Kalman filtering technique with a fixed-lag smoother is used for simultaneously filtering the noise and estimating the signal derivatives. The algorithm is implemented on a F-16 fighter aircraft model performing a reverse-turn maneuver, where both control angles and control rates present relevant variations. The reported results show that the effect of a step variation of commanded load factor and/or roll angle on the aircraft position at following times can be determined in real-time and displayed to the pilot.