In principle, the Automatic Identification System (AIS) makes covert rendezvous at sea, such as smuggling and piracy, impossible; in practice, AIS can be spoofed or simply disabled. Previous work showed a means whereby such deviations can be spotted. Here we play the opponent's side, and describe the least-detectable trajectory that the elusive vessel can take. The opponent's route planning problem is formalized as a non-convex optimization problem capitalizing the Kullback-Leibler (KL) divergence between the statistical hypotheses of the nominal and the anomalous trajectories as key performance measure. The velocity of the vessel is modeled with 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 globally-optimal and computationally-efficient technique, called the Non-Convex Optimized Stealth Trajectory (N-COST) algorithm. The N-COST algorithm consists amounts to solving multiple convex problems, with the number proportional to the number of segments of the piecewise OU trajectory. The effectiveness of the proposed approach is demonstrated through case studies and a real-world example.

Optimal Opponent Stealth Trajectory Planning Based on an Efficient Optimization Technique

Braca P.;De Maio A.;Millefiori L. M.;
2021

Abstract

In principle, the Automatic Identification System (AIS) makes covert rendezvous at sea, such as smuggling and piracy, impossible; in practice, AIS can be spoofed or simply disabled. Previous work showed a means whereby such deviations can be spotted. Here we play the opponent's side, and describe the least-detectable trajectory that the elusive vessel can take. The opponent's route planning problem is formalized as a non-convex optimization problem capitalizing the Kullback-Leibler (KL) divergence between the statistical hypotheses of the nominal and the anomalous trajectories as key performance measure. The velocity of the vessel is modeled with 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 globally-optimal and computationally-efficient technique, called the Non-Convex Optimized Stealth Trajectory (N-COST) algorithm. The N-COST algorithm consists amounts to solving multiple convex problems, with the number proportional to the number of segments of the piecewise OU trajectory. The effectiveness of the proposed approach is demonstrated through case studies and a real-world example.
Aubry, A.; Braca, P.; D'Afflisio, E.; De Maio, A.; Millefiori, L. M.; Willett, P.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/1143979
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact