Applying Advanced Analytical Capability to Extract Features from MDA Historical Test Data

Advanced data algorithmic techniques are revolutionizing many commercial and military products. These techniques show promise to rapidly improve US missile defense, potentially allowing the integrated BMDS the ability to perform time critical operations more quickly, extract from observational sensor data new discriminating characteristics that allow identification of threat and threat features, predict the likely occurrence of an event or weapon intent, and improve resiliency to intentional or unintentional surprise during mission execution. A unique source for these analytical innovations lies in work Arete has conducted for the Intelligence Community, where analytical techniques commonly address subtle target situations to extract key information. Proven sensor fusion, artificial intelligence, and detection algorithms can be adapted to apply to the BMDS. Data to prove algorithmic efficacy is readily available from the investment that the US has made in Missile Defense testing. Terabytes of sensor test data are available from previous MDA missions, which may unlock valuable new and improved performance from existing sensors and systems. This project explores data analysis to show the value and application of data methods to improve BMDS performance. Areté will investigate capabilities using MDA test data, applying adapted data algorithms and methodologies to form a kernel of capabilities. Approved for Public Release | 18-MDA-9710 (6 Jul 18)