Optimal Stealth Trajectory Design to Deceive Anomaly Detection Process
Enrica d’Afflisio, Augusto Aubry, Paolo Braca, Antonio De Maio, Leonardo Maria Millefiori · OCEANS 2019 - Marseille · 2019
A new methodology is proposed to deceive an anomalous trajectory detector by designing ship paths that deviate from the nominal traffic routes in an optimized way. The route planning is formalized as a min-max problem (with respect to surveillance system acquisition instants) focusing on the Kullback-Leibler (KL) divergence between the statistical hypotheses of the nominal and the anomalous trajectories as key performance measure. Modeling the vessel's dynamic according to the Ornstein-Uhlenbeck (OU) mean-reverting stochastic process, physical, practical, and kinematic requirements are also accounted for forcing several constraints at the design stage. A computationally efficient technique is proposed to handle the resulting non-convex optimization problem, and some case studies are reported to assess its effectiveness.