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As the U.S. military transforms to an information-based force, it will need processes and methods to collect, combine, and utilize the intelligence that is generated by its assets. The process known as fusion will play an important role in determining whether this intelligence is used in the most beneficial manner. The process of fusion, combining pieces of information to produce higher-quality information, knowledge, and understanding, is often poorly represented in constructive models and simulations that are used to analyze intelligence issues. This report describes one approach to capturing the fusion process in a constructive simulation, providing detailed examples to aid in further development and instantiation. The sequential fusion method in intended to determine whether separate intelligence observations are close enough geographically, have consistently identified the same battlefield entity, and contain high-quality information, all of which must be considered before fusion of intelligence can occur. The fusion process described in this report is, for the most part, an implicit representation of the generation of battlefield intelligence and can be used in a constructive simulation or fusion model to better understand the dynamics of intelligence-gathering systems and their effect on intelligence metrics.

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The research described in this report was sponsored by the United States Army and conducted by the RAND Arroyo Center.

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