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Cited by 10Target Tracking and Data Fusion in Sensor NetworksVideo Surveillance and Tracking MethodsInertial Sensor and Navigation

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Heterogeneous Information Fusion for Multitarget Tracking Using the Sum-product Algorithm

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Soldi, Giovanni, Gaglione, Domenico, Meyer, Florian, Hlawatsch, Franz, Braca, Paolo, Farina, Alfonso, Z. Win, Moe·2019·ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
DOI 10.1109/icassp.2019.8683891
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Abstract

The sum-product algorithm (SPA) was recently shown to provide a scalable methodology for multitarget tracking (MTT) using multiple sensors. Here, we focus on another advantage of the SPA frame-work, namely, its capacity for Bayesian fusion of heterogeneous data sources and auxiliary information. We develop extensions of the SPA-based multisensor MTT algorithm that integrate data from an auxiliary surveillance system and geographic information about standard target routes. The effectiveness of our approach is demonstrated for a simulated scenario and for a real maritime 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 [53]

    The Introduction and Section 3 describe extending SPA-based multitarget tracking to integrate AIS reports, and Section 6 reports radar–AIS fusion using real data. Our copy does not identify the AIS data as coming from a satellite-based (Sat-AIS) system, so it supports AIS fusion but not that specific source. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

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Citations

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No references could be resolved yet.

Research works printed but not linked: 27

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  2. 10.1109/TAES.2015.130550 · DOI
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  18. mahler, 2007, Statistical Multisource-Multitarget Information Fusion
  19. 10.1109/TAES.2012.6324726 · DOI
  20. bar-shalom, 2011, Tracking and Data Fusion A Handbook of Algorithms
  21. 10.1109/MCOM.2014.6815901 · DOI
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  25. schuhmacher, 2008, On performance evaluation of multi-object filters, 2008 11th International Conference on Information Fusion FUSION, 1
  26. 10.1109/MSP.2015.2504328 · DOI
  27. 10.1109/MSP.2018.2845907 · DOI

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Metadata

Authors
Soldi, G., Gaglione, D., Meyer, F., Hlawatsch, F., Braca, P., Farina, A., & Z. Win, M.
Affiliations
  • NATO Centre for Maritime Research and Experimentation (IT)
  • Massachusetts Institute of Technology (US)
  • TU Wien (AT)
  • Professional Consultant, Rome, Italy
  • Laboratory for Information and Decision Systems, MIT, Cambridge, MA, USA
ORCID
Venue
ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher
IEEE
Published
2019-05
Pages
5471-5475
ISSN
1520-6149 (ISSN-L)
DOI
10.1109/icassp.2019.8683891
OpenAlex
W2939535628
Cited by
10
References
0
Citations by year
2025: 1 · 2024: 2 · 2023: 1 · 2021: 3 · 2020: 2 · 2019: 1
FWCI
0.57
Type
conference paper
Language
en
Open access
Licence
Locations
  • IEEE International Conference on Acoustics Speech and Signal Processing (publishedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
Funders
  • Grantová Agentura České Republiky (GA17-19638S)
  • Austrian Science Fund (J3886, P32055, P27370)
  • Defense Advanced Research Projects Agency (N66001, N66001-19-C-4004, N66001-19)
  • U.S. Navy
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Target Tracking and Data Fusion in Sensor Networks
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
  • Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
Keywords
multi-target tracking, sum-product algorithm, heterogeneous data fusion, Bayesian fusion, sensor fusion, maritime surveillance, target trajectory estimation

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