Partial Aircraft State Estimation from Visual Motion Using the Subspace Constraints Approach

The estimation of an aircraftmotionfrom the optical  ow observed by a downward-lookingbody-Ž xed camera is discussed. 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, giving rise to a nonlinear estimation problem. The problem was solved using an implicit extended Kalman Ž lter. The suggested algorithmwas implemented in a simulation,which veriŽ ed that the angle of attack, the angle of sideslip, and the angular body pitch, yaw, and roll rates could be estimated. The estimation was shown to be unbiased with a Monte Carlo method. Furthermore, the standard deviations of the estimation errors converged to reasonable values after a relatively small time interval. An important feature of the method is that good performance was achieved even when tracking a relatively small number of feature points, implyingmodest real-time computational needs. The estimated signals could be used either for navigationor control.