This paper discusses the motion estimation of a general aviation airplane using 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, giving rise to a nonlinear estimation problem that is solved using an implicit extended Kalman filter. The suggested algorithm was implemented in a simulation. A Monte-Carlo analysis showed that the estimation was unbiased. 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, implying modest real-time computational needs. The algorithm is more efficient than previously published works, in the sense that it does not require pre-storage of a terrain profile or the use of a stabilized camera.


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    Title :

    Aircraft state estimation from visual motion: application of the subspace constraints approach


    Contributors:
    Rotstein, H. (author) / Gurfil, P. (author)


    Publication date :

    2002-01-01


    Size :

    762681 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English






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    Soatto, S. / Perona, P. | British Library Online Contents | 1997