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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) ...
Maritime situational awareness use cases enabled by space-borne sensors
(CMRE, 2019/06)
This paper discusses a technique for predicting a vessel?s position over a long time horizon with much lower uncertainty than current methods. Lowering the uncertainty of long-range prediction is a key challenge in maritime ...
Belief propagation based AIS/radar data fusion for multi-target tracking
(CMRE, 2019/05)
A data fusion technique aiming at combining observations from two classes of sensors is proposed. The first class consists of sensors that produce periodic noisy observations of the targets; moreover, they may also miss ...
The impact of sea state on HF surface-wave radar ship detection and tracking performances
(CMRE, 2019/06)
Nowadays, we face an ever increasing interest in new technologies and solutions for the maritime surveillance (MS) domain. In such a context, oceanographic high-frequency surface-wave (HFSW) radars have started to get ...
Model performance assessment for long-term vessel prediction using HFSW radar data
(CMRE, 2019/06)
Vessels in open seas are seldom continuously observed. Thus, the problem of long-term vessel prediction becomes crucial. This paper focuses its attention on the performance assessment of the Ornstein- Uhlenbeck target ...
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 ...
Adaptive filtering of imprecisely time-stamped measurements with application to AIS networks
(CMRE, 2019/06)
Driven by real-world issues in maritime surveillance, we consider the problem of estimating the target state from a sequence of observations that can be imprecisely time-stamped. That is, the time between two consecutive ...
Data driven vessel trajectory forecasting using stochastic generative models
(2019/05)
In this work, we propose a data driven trajectory forecasting algorithm that utilizes both recorded historical and streaming trajectory observations. The algorithm performs Bayesian inference on a directed graph the walks ...
Validation of the Ornstein-Uhlenbeck route propagation model in the Mediterranean Sea
(CMRE, 2019/06)
Traffic route analysis and prediction are both crucial to maritime security. The ability to predict a vessel position in the future is essential to provide information on upcoming events. However, accurate prediction along ...