This contribution shows that taking into account the error ellipse of the GPS measurement in the hypothesis generation and evaluation steps of the presented multi-hypothesis mapmatching algorithm improves the positioning accuracy in comparison to only including the standard deviation of latitude and longitude error without considering the IMU. Thus, it can be concluded that taking into account additional information on the GPS position quality in the map-matching algorithm enables an alternative for including additional sensors, which cause additional cost, in the positioning system. This accuracy is enough for most applications. Assuming that the positioning has to be track-selective at the latest at the clearance point, the measurements exemplarily applied to the presented algorithm show that the algorithm has the potential to fulfil the accuracy requirement. However, the accuracy obtained from additionally including the IMU cannot be achieved with only including the GPS (including the error ellipse parameters) and radar data in the presented algorithm. It should be pointed out that the result of the positioning algorithm is also more precise than the one of the basic algorithm if the modification is only applied to the hypothesis evaluation step but not to the generation step.


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    Titel :

    Including the error ellipse of GPS measurements in a multi-hypothesis based map-matching algorithm for train positioning


    Beteiligte:


    Erscheinungsdatum :

    2010


    Format / Umfang :

    9 Seiten, 6 Bilder, 9 Quellen


    Anmerkungen:

    (nicht paginiert)


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Datenträger


    Sprache :

    Englisch




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