Persistent Maritime Target Tracking Using Automated Target Fingerprinting and Discrimination Navy SBIR FY2014.1 Sol No.: Navy SBIR FY2014.1 Topic No.: N141-016 Topic Title: Persistent Maritime Target Tracking Using Automated Target Fingerprinting and Discrimination Proposal No.: N141-016-0818 Firm: Lambda Science, Inc. P.O. Box 238 Wayne, Pennsylvania 19087 Contact: Joseph Teti Phone: (610) 581-7940 Web Site: www.lamsci.com Abstract: Per the topic description, dense maritime environments pose significant challenges to naval airborne sensor systems with respect to surface target classification, track lifetime, and track association. A promising strategy to drastically improve situational awareness and reduce operator workload in these environments is to utilize a Feature Aided Tracking and Discrimination (FAT-D) capability in conjunction with a sensor suite resource manager (RM) that interleaves high range resolution (HRR) pulses within the sensor's primary search mode, and maintains and manages information about the surface contact picture on much larger timescales. RM operates on multiple timescales ranging from relatively short-term track updates that include classification dwells, extending to much longer time periods that involve re-associations after long duration track breaks or encounters that can span multiple missions. Benefits: The ability to form re-associations on merged tracks that separate, long track gaps and encounter association across missions. Return