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Automated recognition challenges for wide-area motion imagery

Automated pattern recognition has been around for several decades. Generally we have been successful at tackling a large variety of technical problems. This paper presents the challenges inherent in wide area motion imagery, which is problematic to the normal pattern recognition process and associated pattern recognition systems. This paper describes persistent wide area motion imagery, its role as a manifold for overlaying episodic sensors of various modalities to present a better view of activity to an analyst. An underlying framework, SPADE, is introduced and a layered sensing viewer, Pursuer, is also presented to demonstrate the utility of creating a unified view of the sensing world to an analyst.