A real-time track classifier based on fuzzy logic is presented. The application deals with false alarm rejection in an airborne infra-red search and track (IRST) system. The approach is based on the use of a set of rules representing heterogeneous knowledge on behavior and appearance of physical objects. Uncertainty rules are considered to model knowledge on classes, while gradual rules are used to compute some auxiliary variables. Examples of rules are given, as well as results on simulated data.


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    Title :

    Tracks real-time classification based on fuzzy rules


    Contributors:
    Ayoun, A. (author) / Grabisch, M. (author)

    Published in:

    Publication date :

    1997


    Size :

    12 Seiten, 4 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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