This paper outlines an approach and experimental results for synthetic aperture radar (SAR) object recognition using the MSTAR data. With SAR scattering center locations and magnitudes as features, the invariance of these features is shown with object articulation (e.g., rotation of a tank turret) and with external configuration variants. This scatterer location and magnitude quasi-invariance is used as a basis for development of a SAR recognition system that successfully identifies articulated and non-standard configuration vehicles based on non-articulated, standard recognition models. The forced recognition results and pose accuracy are given. The effect of different confusers on the receiver operating characteristic (ROC) curves are illustrated along with ROC curves for configuration variants, articulations and small changes in depression angle. Results are given that show that integrating the results of multiple recognizers can lead to significantly improved performance over the single best recognizer.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Object recognition results using MSTAR synthetic aperture radar data


    Beteiligte:
    Bhanu, B. (Autor:in) / Jones, G. (Autor:in)


    Erscheinungsdatum :

    01.01.2000


    Format / Umfang :

    422875 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Object Recognition Results Using MSTAR Synthetic Aperture Radar Data

    Bhanu, B. / Jones, G. / IEEE | British Library Conference Proceedings | 2000


    MSTAR Requirements and Reference Design

    J. E. Hanson / B. A. Jaroux | NTIS | 2014


    mSTAR Requirements and Reference Design

    Hanson, John Eric / Jaroux, Belgacem Amar | NTRS | 2014


    SEASAT Synthetic Aperture Radar Data

    Henderson, F. M. | NTRS | 1981


    Synthetic Aperture Radar

    Doerry, A. W. / Dickey, F. M. | British Library Online Contents | 2004