Autonomous navigation of airborne platforms requires the integration of diverse sources of sensor data and contextual information. In this paper we describe a system that utilizes polarimetric radar cross-section and range data to generate position estimates based on four kinds of information: area segmentation, ground contours, landmarks and road networks. Ground truth in the form of terrain feature maps is correlated with each type of data stream. Finally, an arbitrator integrates these inputs with contextual knowledge about the preplanned flight path to resolve conflicts and arrive at a final estimate of current position.


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    Title :

    An Intelligent System For Autonomous Navigation Of Airborne Vehicles


    Contributors:

    Conference:

    Sensor Fusion: Spatial Reasoning and Scene Interpretation ; 1988 ; Boston,MA,United States


    Published in:

    Proc. SPIE ; 1003 ; 451


    Publication date :

    1989-01-05





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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