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| Content Provider | IET Digital Library |
|---|---|
| Author | Gaglione, Domenico Soldi, Giovanni Meyer, Florian Hlawatsch, Franz Braca, Paolo Farina, Alfonso Win, Moe Z. |
| Abstract | The goal of maritime situational awareness (MSA) is to provide a seamless wide-area operational picture of ship traffic in coastal areas and the oceans in real time. Radar is a central sensing modality for MSA. In particular, oceanographic high-frequency surface-wave (HFSW) radars are attractive for surveying large sea areas at over-the-horizon distances, due to their low environmental footprint and low power requirements. However, their design is not optimal for the challenging conditions prevalent in MSA applications, thus calling for the development of dedicated information fusion and multisensor-multitarget tracking algorithms. In this study, the authors show how the multisensor-multitarget tracking problem can be formulated in a Bayesian framework and efficiently solved by running the loopy sum-product algorithm on a suitably devised factor graph. Compared to previously proposed methods, this approach is advantageous in terms of estimation accuracy, computational complexity, implementation flexibility, and scalability. Moreover, its performance can be further enhanced by estimating unknown model parameters in an online fashion and by fusing automatic identification system (AIS) data and context-based information. The effectiveness of the proposed Bayesian multisensor-multitarget tracking and information fusion algorithms is demonstrated through experimental results based on simulated data as well as real HFSW radar data and real AIS data. |
| Starting Page | 1845 |
| Ending Page | 1857 |
| Page Count | 13 |
| ISSN | 17518784 |
| Volume Number | 14 |
| e-ISSN | 17518792 |
| Issue Number | Issue 12, Dec (2020) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-rsn/14/12 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2019.0508 |
| Journal | IET Radar, Sonar & Navigation |
| Publisher Date | 2020-08-07 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Authors Bayes Method Bayesian Framework Bayesian Information Fusion Central Sensing Modality Coastal Areas Computer Vision And Image Processing Technique Context-based Information Data And Information; Acquisition, Processing, Storage And Dissemination in Geophysics Dedicated Information Fusion Digital Signal Processing Geophysical Signal Processing Geophysics Computing HFSW Radar Data High-frequency Surface-wave Radars Information Fusion Algorithm Instrumentation And Technique For Geophysical, Hydrospheric And Lower Atmosphere Research Knowledge Engineering Technique Loopy Sum-product Algorithm Low Environmental Footprint Low Power Requirements Marine Radar Maritime Situational Awareness MSA Application Multisensor-multitarget Tracking Problem Oceanographic And Hydrological Technique And Equipment Oceanographic Technique Over-the-horizon Distances Probability Theory Radar Detection Radar Equipment Radar Tracking Sea Areas Sensor Fusion Ship Traffic Ships Signal Processing And Detection Statistics Stochastic Linearised SCUC Suitably Devised Factor Graph System And Application Target Tracking Tracking Algorithm Wide-area Operational Picture |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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