Enhanced Target Identification (ETID) for Strategic HEL Systems Using Bayesian-Topological Fusion Classification.

"This proposal addresses the development of an enhanced target identification (ETID) method of classifying and identifying boost phase threat objects for targeting by a strategic HEL weapon such as a Space Based Laser (SBL), a Ground Based Laser (GBL) or anAirborne Laser (ABL) weapon.The work to be accomplished builds on past work on Target Identification (TID) algorithms accomplished for the Air Force Research Laboratory (AFRL) Information Fusion (IF) Directorate. Under previous work, a concept for an ETID algorithm was formulatedand preliminary design work was accomplished. However, due to funding reductions from BMDO, the actual full design, implementation, and testing of the ETID algorithm was not accomplished. We propose to finish the work on the ETID algorithm by completingthe full algorithm design, developing the full algorithm for the current HEL weapon systems designs and missions, and testing the full algorithm using simulated and real threat data as available.The outputs of the Phase I program will be a prototype Enhanced Target Identification Algorithm, a detailed performance assessment of the ETID algorithm, and a plan for Phase II development of an operational algorithm. The proposed program would take a significant step toward solving one of the most difficult problems for SBL sensor, tracking, and weapon systems, that of identifying targets during an engagement. The resulting ETID algorithm technology could