Ever-increasing data rates and data volumes associated with proposed large ground data processing/support systems for advanced sensor applications have made the costs of resultant data processing and analysis almost prohibitive. Though the prospective experimenter is most well-intentioned and well-motivated, he or she is immediately faced with a planner's dilemma: What is wanted, versus what budget and technology can provide. It has become obvious that the system user needs help early in project planning to meaningfully understand the impact of requirements on potential costs. With this helpful information available in a parametric form, the scientist-in-charge could make intelligent trade offs between scientific value and ultimate costs in the initial stages, thus assuring maximum return on dollar cost. Parametric analysis includes an initial scoping of the pertinent parameters to reduce the analysis to manageable proportions. An analysis of these crucial parameters leads to the choice of parameter sets which characterize the major system alternatives. These parameter sets are then used to define systems which cover the spectrum of expected values and which are representative of major classes of systems sharing common attributes. What is known and what must be assumed will be distinct for different situations by virtue of diverse development schedules, objectives, expected operational time-frames, historical precedents, etc.
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