Multi-target tracking algorithms using a probabilistic data association are state-of-the-art for current automotive safety applications. When using sensors with good resolution capabilities, probabilistic data association hypotheses are complete. However, with limited sensor resolution, measurements may not be resolved. This leads to degraded association hypotheses and wrong state innovations using standard algorithms. In this paper, the benefit of integrating sensor resolution in the data association and filter innovation is shown by a comparison of an advanced algorithm and the standard approach. The total root mean square error (RMS) of position, velocity, and time to collision (TTC) of all targets are decreased by the proposed algorithm when targets are merged. Thus, this paper suggests that sensor resolution should always be modeled by multi-target tracking algorithms in automotive environments to gain superior results.


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    Title :

    Influence of sensor resolution on time critical automotive applications


    Additional title:

    Einfluß des Sensorauflösungsvermögen auf zeitkritischen Anwendungen im Fahrzeug


    Contributors:


    Publication date :

    2010


    Size :

    6 Seiten, 10 Bilder, 2 Tabellen, 13 Quellen


    Remarks:

    (nicht paginiert)


    Type of media :

    Conference paper


    Type of material :

    Storage medium


    Language :

    English




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