System-level Post Intercept Assessment

When targeting an enemy threat, it is very important to know how effective the intercept was so as to make decisions on how to proceed. Pre-intercept information may be subject to uncertainty or accuracy considerations, meaning that a pre-intercept effectiveness assessment should be refined by post-intercept sensor data. Toyon Research Corporation and Modern Technology Solutions, Inc. (MTSI) propose a solution that uses data from multiple sensors when available to perform this post-intercept effectiveness assessment enhancement. Features based on the post-intercept scene will be constructed via investigation of physically-rigorous simulated interception scenes. The extraction of these features in an automated fashion will be implemented via a particle probability hypothesis density filter that can obtain kinematic tracks in a system in which the number and distribution of tracks is not known. Using physics-based simulated data and the automated feature extraction, intercept effectiveness and associated variables will be parameterized. Fusion of different sensor modalities in order to result in an estimate of the effectiveness will be performed via probabilistic statistical modeling. Toyon and MTSI will create physically reasonable scenes for testing in order to demonstrate the superior capability of our algorithms to robustly estimate the effectiveness of an intercept over pre-intercept assessments. Approved for Public Release | 16-MDA-8917 (15 November 16)