Future safety and comfort systems will require clearly enhanced capabilities for environmental sensing and traffic scene understanding. This contribution points out the potential of millimeter-wave radar sensors with high spatial resolution and high sensitivity for this demanding task and addresses some aspects of practical implementation. The enhanced perception capabilities of imaging radar in traffic environment are demonstrated, and automatic scenario interpretation, involving methods of image processing, is described. It comprises sensor motion, road course prediction and object segmentation with regard to the realization of new mobile applications. This contribution describes methods for forward looking traffic scene interpretation to determine road course and objects up to a distance of 150 meters based on high resolution radar images. To attain this goal the informations 'roadsides' and 'moving objects' are extracted from the images and processed in two additional modules. The road course estimation is performed by adapting a clothoidal road model to the pre-processed data. This constitutes a combinatorial optimization problem, which is solved using a particle filter approach. The regions, which are segmented in the Doppler matrix by a connected component algorithm, are evaluated in the object detection step. The object-related attributes position, size, shape, and velocity are derived from these segments and can be classified and tracked over time. This is accomplished by a simple Kalman-filter in combination with two-dimensional data association methods.


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    Titel :

    Information retrieval capabilities of high-resolution mobile radar


    Weitere Titelangaben:

    Möglichkeiten der Informationsrückgewinnung bei einem hochauflösenden, mobilen Radar


    Beteiligte:
    Meis, Urban (Autor:in) / Schneider, Robert (Autor:in)


    Erscheinungsdatum :

    2005


    Format / Umfang :

    5 Seiten, 5 Bilder, 11 Quellen


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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