Multi-Classifier Target Identification (MCTID)

Target identification for the boost and early ascent (BEA) phase, and the midcourse (MC) phase is one of the most challenging problems for the BMDS. The Multi-Classifier Target Identification project employs two synergistic classifier techniques - a probabilistic Bayesian Classifier and a deterministic Topological Classifier – to develop target classifications using weighted target features. These individual classifications, together with outside classifications, are then fused, based on adaptive weightings, to produce a final classification. Phase I testing against realistic simulated data showed promise for both BEA and MC threats. In this Phase II effort, the MCTID technology will be developed by The CORE Group team, and tested in the MDA X-Lab against real recorded and live BEA data. Development and testing will be accomplished in two threads- one using Overhead Non-imaging Infrared (ONIR) data only as provided by the Common Mission System (CMS) from Lockheed Martin IS&S, and the second using a more robust set of real and simulated sensor data sources from current and planned BMDS sensors. Development will include a TID operator interface employing a state-of-the-art human machine interface (HMI). The MCTID will be hosted on a Field Test Unit (FTU) for testing at multiple sites.