Exploitation of Networked Sensor Phenomenology Involving Robust Estimation (ENSPIRE)

One of the primary research objectives for multi-sensor data fusion within the Ballistic Missile Defense System (BMDS) is the development of novel techniques to enable robust target discrimination. While great strides have been made in recent years to advance capabilities through the use of features available from Forward Based Radars (i.e. AN/TPY-2 and SBX) and emerging optical platforms (i.e. ABIR and PTSS), these algorithms remain coupled to a priori assumptions regarding the lethality characteristics of targets. In a world in which threat characteristics are constantly evolving, it is imperative to develop a target discrimination solution which explicitly separates these internal assumptions the lethal hypothesis from the estimation of physical attributes. In response to this technology need, ExoAnalytic Solutions Inc. proposes ENSPIRE: Exploitation of Networked Sensor Phenomenology Involving Robust Estimation. The objectives of ENSPIRE are: 1) to develop algorithms that adaptively define and solve hierarchical statistical models that link sensor feature data to target attributes through causal physics; 2) to develop an algorithm that combines target attribute estimates with a lethal hypothesis to perform discrimination; and 3) to leverage recent advancements in Information Theory to develop an analytical framework for conducting disciplined trade studies to assess the performance of ENSPIRE.