Plume EO-RCS Data Fusion

The use of models to predict exhaust plume observables such as electro-optical (EO) signatures or radar cross section (RCS) is an integral part of many missile defense activities due to the limited quantity and extent of flight measurements on domestic and foreign missiles. The potential exists to enhance the fidelity of plume modeling by fusing information from multiple sensor measurements in EO and RCS space in order to extract and validate essential features of plume phenomenology common to both. Data fusion is analogous to humans using multiple senses (sight, smell, sound, taste, etc) to more accurately recognize something. When applied to missile defense, fusing data from multiple sensors and extracting relevant features, aims to locate, characterize, and identify a missile threat with more speed and accuracy than what can be accomplished with data from a single source. In addition, data from multiple sources such as electro-optical and radar sensors provide complementary measurements of plume properties. When used together these can provide a more comprehensive description of the underlying plume phenomenology, which is critical to improving next generation plume modeling fidelity.