22 May 2014 Probabilistic multi-source multi-INT intel fusion benefit analysis
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Abstract
The Process for Probabilistic Multi-Source Multi-INT Intel Fusion Benefit Analysis** (PIFBA) provides a methodology for statistically computing the probability of detecting, locating, and tracking objects in order to assess current capabilities or the benefit of adding or removing ISR assets in order to obtain the statistically optimal result. The PIFBA process defines the approach to calculate the probabilistic benefits or rewards associated with integrating or fusing multisource multi-INT products across a wide range of platforms, sensors, environmental conditions and target objects. This process applies to analyzing ISR capabilities, effectiveness, and gaps, as well as the benefits of applying existing or new technology and tactics. The PIFBA process was designed to answer the following questions:  Based on the defined ISR assets – what is the probability that we know a piece of Intel with sufficient accuracy and timeliness to be of value to the analyst or warfighter?  What is the benefit of adding new data via additional platforms, sensors, or processing?  What is the benefit of adding new systems or technology and to what degree of performance must they exhibit in order to affect the statistical outcome?
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David Wisniewski, David Wisniewski, Paul Hershey, Paul Hershey, } "Probabilistic multi-source multi-INT intel fusion benefit analysis", Proc. SPIE 9121, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2014, 912105 (22 May 2014); doi: 10.1117/12.2049723; https://doi.org/10.1117/12.2049723
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