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Belief propagation based AIS/radar data fusion for multi-target tracking
Abstract
A data fusion technique aiming at combining observations from two classes of sensors is proposed. The first class consists of sensors that produce periodic noisy observations of the targets; moreover, they may also miss the targets or generate false alarms. Sensors belonging to the second class, instead, do not generate false alarms, and provide aperiodic noisy observations of the targets that may have an identity. The problem is formalised with specific application to the maritime domain, in which radar sensors and the Automatic Identification System (AIS) are selected as representatives of the two classes, respectively. A Bayesian framework is developed and a detection-estimation problem is formulated, which is then efficiently solved with the use of a Belief Propagation (BP) message passing scheme. The performance and the effectiveness of the proposed algorithm is evaluated in a simulated scenario.
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The SPA-based MTT algorithm can be extended to fuse information coming from a Sat-AIS system.
“The SPA-based MTT algorithm can also be extended to fuse information coming from a Sat-AIS system [53], [54].”
From Space-Based Global Maritime Surveillance. Part II: Artificial Intelligence and Data Fusion Techniques (2021) · cites this paper as [54]
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Research works printed but not linked: 19
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Cited by
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Soldi, G., Gaglione, D., Forti, N., Millefiori, L. M., Braca, P., Carniel, S., Simone, A. D., Iodice, A., Riccio, D., Daffina, F. C., et al. (2021) · IEEE Aerospace and Electronic Systems Magazine · doi:10.1109/maes.2021.3070884 · Cited by 44
“, ship’s position and the MMSI identifier [55], [56].”
BackgroundMethodSelf-citationBayesian information fusion and multitarget tracking for maritime situational awareness
Gaglione, D., Soldi, G., Meyer, F., Hlawatsch, F., Braca, P., Farina, A., & Win, M. Z. (2020) · IET Radar, Sonar & Navigation · doi:10.1049/iet-rsn.2019.0508 · Cited by 36
Self-citation
Metadata
- Authors
- Gaglione, D., Braca, P., & Soldi, G.
- Affiliations
- NATO Centre for Maritime Research and Experimentation (IT)
- Venue
- 2018 21st International Conference on Information Fusion (FUSION)
- Publisher
- IEEE
- Published
- 2018-07
- Pages
- 2143-2150
- OpenAlex
- W2891416092
- Cited by
- 37
- References
- 0
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 4 · 2023: 6 · 2022: 3 · 2021: 7 · 2020: 5 · 2019: 3
- FWCI
- 1.51
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Information Fusion (FUSION) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Target Tracking and Data Fusion in Sensor Networks
- Physical Sciences › Engineering › Aerospace Engineering › Radar Systems and Signal Processing
- Physical Sciences › Computer Science › Computer Networks and Communications › Distributed Sensor Networks and Detection Algorithms
- Keywords
- multi-target tracking, data fusion, belief propagation, Automatic Identification System, radar, maritime surveillance, false alarms, target identity, message passing
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