Hybrid and Feature-Aided Multiple Hypothesis Correlation with Ambiguity Assessment

In our Phase I program, Numerica developed a prototype for a hybrid and feature-aided multiple hypothesis correlation (HMHC) system that provides a framework to address several deficiencies in the Ballistic Missile Defense System (BMDS). During the last two years, Numerica has partnered with the Missile Defense National Team-B (MDNTB) through the prime contractor, Lockheed Martin, to support track processing needs within the Command, Control, Battle Management, and Communications (C2BMC) suite of the BMDS. In this time, Numerica has worked on a track-to-track correlation system called Multiple Hypothesis Correlation (MHC). In our Phase II effort, we propose to integrate the HMHC algorithm into the C2BMC suite of the BMD Benchmark by adding its hybrid fusion functionality to the MHC algorithm, which has been identified as the Spiral 6.2 C2BMC track correlator. We also propose to enhance the HMHC system by adding feature-aided track correlation and improving its ambiguity assessment, track initiation, and decorrelation algorithms. A key in this proposed HMHC Phase II program is that synergism is planned with the MHC developments for MDNTB. The innovative, but higher complexity, concepts desired by MDNTB that require longer-term development will be pursued in the SBIR Phase II effort. Since Numerica has direct access to the MHC and can rapidly integrate any successful HMHC solutions, the SBIR program will provide a means for rapid transition of the technology into the C2BMC.