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Performance assessment of vessel dynamic models for long-term prediction using heterogeneous data
(CMRE, 2019/06)
Ship traffic monitoring is a foundation for many maritime security domains, and monitoring system specifications underscore the necessity to track vessels beyond territorial waters. However, vessels in open seas are seldom ...
Detecting anomalous deviations from standard maritime routes using the Ornstein-Uhlenbeck process
(CMRE, 2019/05)
A novel anomaly detection procedure based on the Ornstein-Uhlenbeck (OU) mean-reverting stochastic process is presented. The considered anomaly is a vessel that deviates from a planned route, changing its nominal velocity ...
Hybrid Bernoulli filtering for detection and tracking of anomalous path deviations
(CMRE, 2019/05)
This paper presents a solution to the problem of sequential joint anomaly detection and tracking of a target subject to switching unknown path deviations. Based on a dynamic model described by Ornstein- Uhlenbeck (OU) ...
Long-term vessel kinematics prediction exploiting mean-reverting processes
(CMRE, 2019/06)
Long-term target state estimation of non-manoeuvring targets, such as vessels under way in open sea, is crucial for maritime security. The dynamics of non-manoeuvring targets is traditionally modelled with a white noise ...
Anomaly detection and tracking based on mean-reverting processes with unknown parameters
(CMRE, 2019/05)
Piecewise mean-reverting stochastic processes have been recently proposed and validated as an effective model for long-term object prediction. In this paper, we exploit the Ornstein-Uhlenbeck (OU) dynamic model to represent ...
Modeling vessel kinematics using a stochastic mean-reverting process for a long-term prediction
(CMRE, 2019/06)
We present a novel method for predicting long-term target states based on mean-reverting stochastic processes. We use the Ornstein-Uhlenbeck (OU) process, leading to a revised target state equation and to a time scaling ...
Scalable distributed change detection and its application to maritime traffic
(CMRE, 2019/06)
Building on a novel methodology based on the Ornstein-Uhlenbeck (OU) process to perform accurate long-term predictions of future positions of ships at sea, we present a statistical approach to the detection of abrupt changes ...
Maritime anomaly detection based on mean-reverting stochastic processes applied to a real-world scenario
(CMRE, 2019/05)
A novel anomaly detection procedure based on the Ornstein-Uhlenbeck (OU) mean-reverting stochastic process is presented. The considered anomaly is a vessel that deviates from a planned route, changing its nominal velocity ...