3 May 2007 Quantifying an imagery system's performance with transformational mission data analysis
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Traditionally, the performance of an imagery intelligence collection system is quantified by a satisfaction percentage. The mission satisfaction is the number of images collected divided by the number of images requested. This paradigm assumes the information needed is generated from the collected imagery data if the data is delivered on time to the consumer. As persistent surveillance requirements become more prominent, the time sequence of data collection is increasingly important. The satisfaction percentage is not wholly descriptive of a collection system's ability to complete persistent surveillance missions. A metric of imagery data utility that is dependent on the time sequence of data collected is necessary. Booz Allen Hamilton's transformational mission analysis focuses on additional metrics to characterize satisfaction of persistent surveillance requirements. Surveillance missions are based on a need to monitor an activity or event. The observables are animate, and may require a time sequence of images. For surveillance imagery data to be useful, the system must collect the data in required sequence and deliver the information in a timely fashion. Booz Allen defines a utility score to quantify system performance against persistent surveillance missions. The utility score includes the satisfaction percentage, but is sensitive to the time dependences of data. This paper outlines a transformational approach to mission analysis. The paper introduces examples of surveillance missions, and the limited value of satisfaction percentage. It defines data relationships between imagery system capabilities and surveillance missions. Finally, it computes the utility score, and quantifies the performance of an example collection system.
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Alisha W. Mauck, "Quantifying an imagery system's performance with transformational mission data analysis", Proc. SPIE 6555, Sensors and Systems for Space Applications, 65550Z (3 May 2007); doi: 10.1117/12.718648; https://doi.org/10.1117/12.718648

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