An analysis of the performance trade space for multifunction EO-IR systems

As pixels have gotten smaller and focal plane array sizes larger, it may be practical to make EO-IR systems which are inherently multifunctional. A system intended to perform threat warning, pilotage imaging and target acquisition imaging would be a multifunctional system. This notional system could be panoramic or hemispheric, with cameras covering all of space simultaneously. It could save cost and weight over federated systems. However, can all of these disparate tasks be performed successfully by a single system, or will the trade-offs compromise the potential savings? Targeting sensors have typically been designed to create long range, high resolution imagery for detection and identification. The imagery is optimized to suppress the scene/clutter and maximize the target signature. Pilotage sensors have typically been wide field of view, unity magnification systems which maximize scene contrast to enable safe flight. Threat warning sensors are intended to detect non or under resolved (spatially or temporally) targets/events using algorithms, and to discriminate them from clutter or solar glint. The first two applications involve imagery for human operator consumption, while the third feeds algorithms. With these disparate performance goals, there is a wide variety of competing metrics used to optimize these sensors -F/no, FOV/IFOV, frame rate, NETD, NEI, FAR, Probability of Identification, etc. This study is a look at how these performance parameters and system descriptors trade and their relative impacts.