Maritime Traffic Model Aided Tracking

The RDRTec team proposes to study the feasibility of an innovative maritime traffic model based tracker (M-TMBT) that integrates our maritime traffic flow model with our state-of-the-art multiple hypothesis tracker and self-learning technology to capture the complex interaction between the vessels and their environment, and achieve dramatic improvement in track life and accuracy. The resulting track quality will support our ongoing work in maritime classification aid (MCA), which is targeted for integration into the Navy Minotaur environment.The RDRTec team proposed M-TMBT system will increase track life expectancy by more than an order of magnitude over the state-of-the-art trackers. Our sensor-agnostic solution will enable highly automated and rapid post-mission analysis in addition to a radical shift toward real-time interdiction of targets in the most complex maritime environments. The three primary modules of the M-TMBT system include: 1. maritime traffic model; 2. self-learning; and 3. tracker.