With the advent of automatic dependent surveillance (ADS), a detailed model of aircraft crosstrack deviations is required to determine the impact of ADS. The authors present a suitable probability model which is amenable to extrapolation. Normal navigation, degradation, pilot blunders, and failures are characterized by Gaussian density functions with associated standard deviations defined by the physics of the event. The overall model is a weighted sum of these Gaussian error probabilities. Overlap and encroachment probabilities are derived, and the impact of ADS on this model determined. It is shown that, by using the simplest form of ADS, the separation standards can be reduced and in addition, by transmitting a figure of merit (FOM) providing information on failures and degradations, the separation standards can be further reduced. The results suggest an improvement by a factor of two over current separation standards.


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    Title :

    Causal probability model for transoceanic track separations with applications to automatic dependent surveillance


    Additional title:

    Kausale Wahrscheinlichkeitsmodelle fuer die transozeane Nachlaufseparierung zur automatischen abhaengigen Ueberwachung


    Contributors:
    Rome, J.H. (author) / Krishnan, V. (author)


    Publication date :

    1988


    Size :

    13 Seiten, 8 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English






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