23 May 2013 Overview of contextual tracking approaches in information fusion
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Many information fusion solutions work well in the intended scenarios; but the applications, supporting data, and capabilities change over varying contexts. One example is weather data for electro-optical target trackers of which standards have evolved over decades. The operating conditions of: technology changes, sensor/target variations, and the contextual environment can inhibit performance if not included in the initial systems design. In this paper, we seek to define and categorize different types of contextual information. We describe five contextual information categories that support target tracking: (1) domain knowledge from a user to aid the information fusion process through selection, cueing, and analysis, (2) environment-to-hardware processing for sensor management, (3) known distribution of entities for situation/threat assessment, (4) historical traffic behavior for situation awareness patterns of life (POL), and (5) road information for target tracking and identification. Appropriate characterization and representation of contextual information is needed for future high-level information fusion systems design to take advantage of the large data content available for a priori knowledge target tracking algorithm construction, implementation, and application.
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Erik Blasch, Erik Blasch, Jesus Garcia Herrero, Jesus Garcia Herrero, Lauro Snidaro, Lauro Snidaro, James Llinas, James Llinas, Guna Seetharaman, Guna Seetharaman, Kannappan Palaniappan, Kannappan Palaniappan, "Overview of contextual tracking approaches in information fusion", Proc. SPIE 8747, Geospatial InfoFusion III, 87470B (23 May 2013); doi: 10.1117/12.2016312; https://doi.org/10.1117/12.2016312

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