default Optimal stealth path planning in the maritime domain: the worst-case condition analysis when the vessel goes dark

Optimal stealth path planning in the maritime domain: the worst-case condition analysis when the vessel goes dark. D'Afflisio, Enrica; Braca, Paolo; Millefiori, Leonardo; Aubry, Augusto; De Maio, Antonio. CMRE-FR-2020-001. December 2020.

In theory, the Automatic Identification System (AIS) makes covert rendezvous at sea, such as smuggling and piracy, impossible; in practice, AIS can be tampered with or simply disabled. Previous research [2,3] has demonstrated that AIS deviations can be detected. In this report, the authors investigate the most covert trajectory that a malicious vessel can navigate. The route is formalized as a non-convex optimization problem capitalizing on the Kullback-Leibler divergence between the statistical hypotheses of the nominal and the anomalous trajectories as key performance measure. The velocity of the vessel is modelled as an Ornstein-Uhlenbeck (OU) mean reverting stochastic process, and physical and practical requirements are accounted for by enforcing several constraints at the optimization design stage. To handle the resulting non-convex optimization problem, we propose a computationally-efficient technique, called the Non-Convex Optimized Stealth Trajectory (N-COST) algorithm. The N-COST algorithm was derived by solving multiple convex problems, where the number was proportional to the number of segments of the piece-wise OU trajectory. The effectiveness of the approach proposed in this document is demonstrated through case studies and a real-world example.