dc.contributor.author | Vivone, Gemine | |
dc.contributor.author | Millefiori, Leonardo | |
dc.contributor.author | Braca, Paolo | |
dc.contributor.author | Willett, Peter K. | |
dc.date.accessioned | 2019-06-19T09:55:53Z | |
dc.date.available | 2019-06-19T09:55:53Z | |
dc.date.issued | 2019/06 | |
dc.identifier.govdoc | CMRE-PR-2019-065 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.12489/805 | |
dc.description.abstract | 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 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 data | en_US |
dc.format | 5 p. : ill. ; digital, PDF file | en_US |
dc.language.iso | en | en_US |
dc.publisher | CMRE | en_US |
dc.source | In: 2017 IEEE Radar Conference (RadarConf), 08-12 May 2017, Seattle, WA, USA, pp. 243-247, doi: 10.1109/RADAR.2017.7944205 | en_US |
dc.subject | Radar | en_US |
dc.subject | Ornstein-Uhlenbeck stochastic process | en_US |
dc.subject | Target motion | en_US |
dc.subject | Ship motion | en_US |
dc.subject | Ship routing | en_US |
dc.subject | Maritime route prediction | en_US |
dc.subject | High-frequency (HF) radar | en_US |
dc.subject | Automatic Identification Systems (AIS) | en_US |
dc.subject | Uncertainty - Mathematical models | en_US |
dc.subject | Sea surface waves | en_US |
dc.subject | Maritime surveillance | en_US |
dc.subject | Maritime situational awareness | en_US |
dc.title | Model performance assessment for long-term vessel prediction using HFSW radar data | en_US |
dc.type | Reprint (PR) | en_US |
dc.type | Papers and Articles | en_US |