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Homeland Security Application of the Army Soft Target Exploitation and Fusion (STEF)System

机译:国土安全应用陆军软目标剥削和融合(Stef)系统

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A fusion system that accommodates both text-based extracted information along with more conventional sensor-derived input has been developed and demonstrated in a terrorist attack scenario as part of the Empire Challenge (EC) 09 Exercise. Although the fusion system was developed to support Army military analysts, the system, based on a set of foundational fusion principles, has direct applicability to department of homeland security (DHS) & defense, law enforcement, and other applications.Several novel fusion technologies and applications were demonstrated in EC09. One such technology is location normalization that accommodates both fuzzy semantic expressions such as behind Library A, across the street from the market place, as well as traditional spatial representations. Additionally, the fusion system provides a range of fusion products not supported by traditional fusion algorithms. Many of these additional capabilities have direct applicability to DHS.A formal test of the fusion system was performed during the EC09 exercise. The system demonstrated that it was able to (1) automatically form tracks, (2) help analysts visualize behavior of individuals over time, (3) link key individuals based on both explicit message-based information as well as discovered (fusion-derived) implicit relationships, and (4) suggest possible individuals of interest based on their association with High Value Individuals (HVI) and user-defined key locations.
机译:融合系统能与更多的传统的传感器衍生的输入一起可同时基于文本的提取的信息已被开发并在恐怖袭击方案证明是帝国挑战(EC)09运动的一部分。虽然融合系统的开发是为了支持军队军事分析家认为,该系统的基础上,一套基本原则的融合,具有直接适用于国土安全部(DHS)和国防,执法,以及其他applications.Several新的融合技术和部门应用程序是在EC09证明。这样一种技术是位置正常化,从市场的地方,以及传统的空间表示可同时模糊语义表达,如图书馆个正着,一街之隔。此外,该融合系统提供了一系列不通过传统的融合算法支持融合产物。许多这些附加功能有EC09演习中进行直接适用于融合系统的DHS.A正式测试。该系统表明,它能够(1)自动形成轨道,(2)帮助分析可视化随着时间的个人行为,基于这两个明确的基于消息的信息(3)联系的关键人物以及发现的(融合衍生)隐含的关系,以及(4)建议根据他们提供高价值的个人(HVI)和用户自定义键的位置的关联可能的利益个体。

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