The fusion of tracks with different state spaces is referred to as heterogeneous track-to-track fusion (HT2TF). In this paper, we present novel approaches for HT2TF using Covariance Intersection (CI). The underlying idea is to augment the low dimensional track. We investigate whether the augmentation approaches proposed for mode mixing in the Interacting Multiple Model (IMM) algorithm can also be employed for the CI. As the augmentation influences the CI optimization, we compare different optimization variants. Finally, we evaluate the presented approaches for collective perception.


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    Titel :

    Unequal Dimension Track-to-Track Fusion Approaches Using Covariance Intersection


    Beteiligte:
    Allig, Christoph (Autor:in) / Wanielik, Gerd (Autor:in)


    Erscheinungsdatum :

    01.06.2022


    Format / Umfang :

    1910655 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch