Blackbox imager characterization, from measurements to modeling range performance

Typically, the modeling of linear and shift-invariant (LSI) imaging systems requires a complete description of each subcomponent in order to estimate the final system transfer function. To validate the modeled behavior, measurements are performed on each component. When dealing with packaged systems, there are many situations where some, if not all, data is unknown. For these cases, the system is considered a blackbox, and system level measurements are used to estimate the transfer characteristics in order to model performance. This correspondence outlines the blackbox measured system component in the Night Vision Integrated Performance Model (NV-IPM). We describe how estimates of performance can be achieved with complete or incomplete measurements and how assumptions affect the final range. The blackbox measured component is the final output of a measurement characterization and is used to validate performance of delivered and prototype systems.