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All objects and activities give off energy in some part of the spectrum, may leave tell-tail signs from their previous activities (e.g., earth scaring or vapor trails), or leave information about relationships that they may have with other entities and activities (e.g., networks). Many of these phenomenologies are either not picked up by current stovepiped sensors, or the data supplied by those sensors are not fully exploited to properly observe them. In either case, new sensor data as well as the better exploitation of existing data could be used to provide, or at least cross cue or correlate with other sensor data to detect, identify, geolocate or track different kind of problems. Current sensors are often designed for specific purposes and are capable of sensing only limited parts of the spectrum. Significantly broadening the sensing spectrum will be an essential element of solving the emerging class of new "hard problems". There are many other observables available that could be exploited to assist in that process. Thus one could broaden the sensing to observe those phenomenologies associated with combustion effluents; thermal radiation; magnetic anomalies; seismic movement; acoustics; unintended electromagnetic emissions, changing weather conditions, logistics support indicators, debris trails; impressed observables (such as tagging); and others. What's needed is a disciplined, analytical process that can map observables to sensors, and ultimately to mission utility. The process, described in this SPIE presentation will address a specific example on the flow from the establishment of requirements to prosecutable observables, to objectives, to identification of sensors and assets, to the allocation of sensors and assets to observables, all based on optimizing mission utility.
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