Traffic Flow and Feature Aided Optimizing Track (TFOT) Navy SBIR FY2016.1 Sol No.: Navy SBIR FY2016.1 Topic No.: N161-004 Topic Title: Traffic Flow and Feature Aided Optimizing Track (TFOT) Proposal No.: N161-004-0246 Firm: Daniel H. Wagner, Associates, Incorporated 559 West Uwchlan Avenue Suite 140 Exton, Pennsylvania 19341 Contact: W. Monach Phone: (757) 727-7700 Web Site: http://www.wagner.com Abstract: The goal of this Traffic Flow and Feature Aided Optimized Tracking (TFOT) project is to develop an efficient and effective target tracker that, using all available data, in particular traffic flow data and non-kinematic features/attributes, can: (1) Generate more persistent, accurate, and actionable tracks, and (2) Be relatively easily integrated into existing airborne (or UAS control) systems. A key enabler for these capabilities is the ability of the advanced (1) Kalman Filter algorithms, (2) multiple hypothesis data association, and (3) Bayesian Network (BN)-based Feature Aided Track Association (FATA) [3] algorithms in TFOT to effectively utilize:  Whatever intelligence is available concerning normal traffic flow in the area of interest, and  Any available sensor non-kinematic (i.e., feature/attribute) data in order to improve data association accuracy, and thus target tracking. Benefits: The use of Traffic Flow and Feature Aided Optimized Tracking (TFOT) would improve the accuracy of the naval surface Situational Awareness (SA) picture, improve the ability to attack threat naval surface platforms, and reduce vulnerability to attack by threat naval surface platforms. In addition, the use of TFOT will significantly reduce operator time-on-task. Return