Browsing Reprints by Subject "Maritime route prediction"
Now showing items 1-15 of 15
-
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 ... -
Bayesian track-to-graph association for maritime traffic monitoring
(CMRE, 2019/05)We present a hypothesis test to associate ship track measurements to an edge of a given graph that statistically models common traffic routes in a given area of interest. The association algorithm is based on the hypothesis ... -
Consistent estimation of randomly sampled Ornstein-Uhlenbeck process long-run mean for long-term target state prediction
(CMRE, 2019/06)In this letter, we study the problem of estimating the long-run mean of the Ornstein-Uhlenbeck (OU) stochastic process and its effect on the long-term prediction of future vessel states, which is a crucial problem for ... -
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 ... -
Data-driven detection and context-based classification of maritime anomalies
(CMRE, 2019/06)Discovering anomalies at sea is one of the critical tasks of Maritime Situational Awareness (MSA) activities and an important enabler for maritime security operations. This paper proposes a data-driven approach to anomaly ... -
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 ... -
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 ... -
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 ... -
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 ... -
Multiple Ornstein-Uhlenbeck processes for maritime traffic graph representation
(CMRE, 2019/05)We propose an unsupervised procedure to automatically extract a graph-based model of commercial maritime traffic routes from historical Automatic Identification System (AIS) data. In the proposed representation, the main ... -
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 ... -
Prediction of rendezvous in maritime situational awareness
(CMRE, 2019/05)In this work, we consider the problem of algorithmically predicting rendezvous among vessels based on their trajectory forecasts in a maritime environment. The problem is treated as hypothesis testing on the expected value ... -
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 ... -
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 ... -
Vessel pattern knowledge discovery from AIS data: a framework for anomaly detection and route prediction
(CMRE, 2014/01)Understanding maritime traffic patterns is key to Maritime Situational Awareness applications, in particular, to classify and predict activities. Facilitated by the recent build-up of terrestrial networks and satellite ...