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Association of radar/SAR ship detections with AIS using the Ornstein-Uhlenbeck process for route propagation: performance metrics and experimental results. Vivone, Gemine; Millefiori, Leonardo; Braca, Paolo; Willett, Peter K.. CMRE-FR-2017-007. November 2018.
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 continuously observed. Thus, the problem of long-term vessel prediction becomes crucial. This re-port focuses attention on the performance assessment of the Ornstein-Uhlenbeck (OU) model for long-term vessel prediction, as compared to usual and well-established nearly constant velocity (NCV) model. Heterogeneous data, such as Automatic Identification System (AIS) data, high-frequency surface wave radar data, and synthetic aperture radar data, are exploited to this aim. Two different association procedures are also presented to cue dwells in case of gaps in the transmission of AIS messages. Suitable metrics have been introduced for the assessment. Considerable advantages of the OU model are pointed out with respect to the NCV model.