System-level Post Intercept Assessment

Performing post-intercept assessment (PIA) is challenging due to the dual problems of first, extracting usable data in a highly cluttered and unpredictable post-intercept environment, and second, fusing that disparate data in a flexible and rapid way. Toyon and Modern Technology Solutions, Inc. (MTSI) propose a two-pronged approach to PIA dealing with the feature-finding and feature-fusion aspects of the problem and the way these two elements of the problem interact; models and simulations will be used that are anchored to flight data and where possible to pre-mission predictions. In the feature-finding regime, feature-finding algorithms based on fragmentation tracking will be further developed from Phase I work and used to extract features of interest in a highly cluttered post-intercept environment. The feature-finding results will be used to structure a Bayesian network for performing feature fusion for fusing different types of evidence. This network will take into account multiple questions of effectiveness. The performance of this Bayesian network will be quantified and bounded, with optimization of parameters of interest. These algorithms will be implemented in a way that allows both in-house testing and testing with the Collaborative Test and Evaluation Center (CTEC).Approved for Public Release | 18-MDA-9522 (23 Feb 18)