19 May 2011 Wide-threat detection: recognition of adversarial missions and activity patterns in Empire Challenge 2009
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Abstract
In this paper, we present results of adversarial activity recognition using data collected in the Empire Challenge (EC 09) exercise. The EC09 experiment provided an opportunity to evaluate our probabilistic spatiotemporal mission recognition algorithms using the data from live air-born and ground sensors. Using ambiguous and noisy data about locations of entities and motion events on the ground, the algorithms inferred the types and locations of OPFOR activities, including reconnaissance, cache runs, IED emplacements, logistics, and planning meetings. In this paper, we present detailed summary of the validation study and recognition accuracy results. Our algorithms were able to detect locations and types of over 75% of hostile activities in EC09 while producing 25% false alarms.
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Georgiy Levchuk, Georgiy Levchuk, Charlotte Shabarekh, Charlotte Shabarekh, Caitlin Furjanic, Caitlin Furjanic, } "Wide-threat detection: recognition of adversarial missions and activity patterns in Empire Challenge 2009", Proc. SPIE 8059, Evolutionary and Bio-Inspired Computation: Theory and Applications V, 80590F (19 May 2011); doi: 10.1117/12.886435; https://doi.org/10.1117/12.886435
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