A new approach for rotation bias removal in the presence of clutter and missed detections is derived that requires a cooperative target. This problem is related to the camera pose estimation problem, and the solution method is based on the formulation for the well-known probabilistic data association filter but executes in a batch mode to avoid convergence on a local maximum. Command and control installations that use multiple hypothesis trackers can apply this approach to correct azimuth and elevation measurements at the multiple hypothesis tracker input by making use of blue force position data within each sensor field of view.


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    Titel :

    Sensor Rotation Bias Removal for Multiple Hypothesis Tracking Applications


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2013-05-31


    Format / Umfang :

    8 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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