In this paper we present a framework for the representation of location information from various sources, such as satellite navigation systems, wireless positioning technologies, beacons, indoor navigation systems, human input, etc. These sources all operate at various degrees of accuracy and often suffer from independent errors. Their output, in terms of the location, can be represented more generally as a probability density distribution (PDF) of the location over a two or three dimensional space - typically Cartesian or other co-ordinates. Combining two or more such PDFs yields a more accurate PDF of the location and improves navigation under difficult circumstances such as indoors or in fading environments. To allow practical deployment of such a framework we define a simple software interface, using the Java programming language, that relies on the transfer of software objects and class files describing the individual PDFs. A number of different positioning sources can thus describe their individual location PDF using a Java class and object, and pass this to other (sub-)devices that have no a-priori knowledge of this PDF for combination with other PDFs.


    Access

    Download


    Export, share and cite



    Title :

    Software Representation for Heterogeneous Data Sources Within A Probabilistic Framework


    Contributors:

    Conference:



    Publication date :

    2001-02-01


    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Object tracking using sensor fusion within a probabilistic framework

    DONGRAN LIU / SNEHA KADETOTAD / MARCOS PAU GERARDO CASTRO et al. | European Patent Office | 2018

    Free access

    Object tracking using sensor fusion within a probabilistic framework

    LIU DONGRAN / KADETOTAD SNEHA / CASTRO MARCOS PAUL GERARDO et al. | European Patent Office | 2018

    Free access

    OBJECT TRACKING USING SENSOR FUSION WITHIN A PROBABILISTIC FRAMEWORK

    LIU DONGRAN / KADETOTAD SNEHA / GERARDO CASTRO MARCOS PAUL et al. | European Patent Office | 2018

    Free access

    A probabilistic framework for traffic data quality

    Ebendt, Rüdiger / Neumann, Thorsten | German Aerospace Center (DLR) | 2018

    Free access