This disclosure describes techniques for using radar cross-section (RCS) data to classify objects detected by autonomous vehicles within driving environments. In some examples, the variance of the RCS data associated with an object may be evaluated to determine signal interference caused by multipath fading. The variance of the RCS data may be used to classify the object and to determine whether the autonomous vehicle can safely drive over the object. For instance, objects such as manhole covers, storm drains, and expansion joints may provide a significant radar signal, but low RCS variance indicating that they can be driven over by the vehicle. Based on the classification of the object, the autonomous vehicle may determine a trajectory around the object or directly over the object.


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    Titel :

    RADAR OBJECT CLASSIFICATION BASED ON RADAR CROSS-SECTION DATA


    Beteiligte:

    Erscheinungsdatum :

    2023-08-03


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G01S RADIO DIRECTION-FINDING , Funkpeilung / G06V



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    Radar cross section studies

    Burnside, W. D. / Dominek, A. K. / Gupta, I. J. et al. | NTRS | 1987


    Radar Cross Section Studies

    W. D. Burnside / A. K. Dominek / I. J. Gupta et al. | NTIS | 1987


    Radar cross section testing

    GARRETSON, III, H. | AIAA | 1986


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