Computer vision-based estimation of aircraft dynamics

This paper discusses the estimation of an aircraft motion from the optical flow observed by a downward-looking body-fixed camera. The estimation is based on the so-called "subspace constraint," which arises when points stationary on the environment are tracked on the image plane. The constraint can be combined with the aircraft dynamics, given rise to a nonlinear estimation problem. In this paper the problem was solved using an implicit extended Kalman filter. The suggested algorithm was implemented in a simulation, which verified that the angle of attack, the angle of sideslip and the angular body pitch, yaw and roll rates could be estimated.