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dc.contributor.authorVivone, Gemine
dc.contributor.authorMillefiori, Leonardo
dc.contributor.authorBraca, Paolo
dc.contributor.authorWillett, Peter K.
dc.date.accessioned2019-06-19T09:55:53Z
dc.date.available2019-06-19T09:55:53Z
dc.date.issued2019/06
dc.identifier.govdocCMRE-PR-2019-065en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12489/805
dc.description.abstractVessels 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 motion model comparing it with the well-established nearly constant velocity model. A gating association procedure and proper performance metrics are introduced to assess the performance using automatic identification system and high-frequency surface wave radar dataen_US
dc.format5 p. : ill. ; digital, PDF fileen_US
dc.language.isoenen_US
dc.publisherCMREen_US
dc.sourceIn: 2017 IEEE Radar Conference (RadarConf), 08-12 May 2017, Seattle, WA, USA, pp. 243-247, doi: 10.1109/RADAR.2017.7944205en_US
dc.subjectRadaren_US
dc.subjectOrnstein-Uhlenbeck stochastic processen_US
dc.subjectTarget motionen_US
dc.subjectShip motionen_US
dc.subjectShip routingen_US
dc.subjectMaritime route predictionen_US
dc.subjectHigh-frequency (HF) radaren_US
dc.subjectAutomatic Identification Systems (AIS)en_US
dc.subjectUncertainty - Mathematical modelsen_US
dc.subjectSea surface wavesen_US
dc.subjectMaritime surveillanceen_US
dc.subjectMaritime situational awarenessen_US
dc.titleModel performance assessment for long-term vessel prediction using HFSW radar dataen_US
dc.typeReprint (PR)en_US
dc.typePapers and Articlesen_US


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