Wavefield Networked Sensing: Principles, Algorithms, and Applications
Networked sensing refers to the capability of multiple wireless terminals to cooperate with the aim of enhancing specific figures of merit, e.g., positioning accuracy or imaging resolution. Regarding radio-based sensing, it is essential to understand when and how sensing terminals should cooperate,...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Open Journal of the Communications Society |
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| Online Access: | https://ieeexplore.ieee.org/document/10811966/ |
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| author | Marco Manzoni Dario Tagliaferri Stefano Tebaldini Marouan Mizmizi Andrea Virgilio Monti-Guarnieri Claudio Maria Prati Umberto Spagnolini |
| author_facet | Marco Manzoni Dario Tagliaferri Stefano Tebaldini Marouan Mizmizi Andrea Virgilio Monti-Guarnieri Claudio Maria Prati Umberto Spagnolini |
| author_sort | Marco Manzoni |
| collection | DOAJ |
| description | Networked sensing refers to the capability of multiple wireless terminals to cooperate with the aim of enhancing specific figures of merit, e.g., positioning accuracy or imaging resolution. Regarding radio-based sensing, it is essential to understand when and how sensing terminals should cooperate, namely the best strategy that trades between performance and cost (e.g., energy consumption, communication overhead, and complexity). This tutorial paper revises networked sensing from a wavefield interaction perspective, aiming to provide a general theoretical benchmark to evaluate its imaging performance bounds and to guide the sensing cooperation accordingly. Diffraction tomography theory (DTT) is the method to quantify the imaging resolution of any radio sensing experiment from inspection of its spectral (or wavenumber) content. In networked sensing, the image formation is based on the back-projection integral, valid for any network topology and physical configuration of the terminals. The wavefield networked sensing is a framework in which multiple sensing terminals cooperate during the acquisition process to maximize the imaging quality (resolution and sidelobes suppression) by pursuing the wavenumber tessellation principle. We discuss all the coherent data fusion possibilities between sensing terminals and possible killer applications. Remarkably, we show the possibility that the proposed method allows obtaining high-quality images of the environment in limited bandwidth conditions, leveraging the coherent combination of multiple multi-static low-resolution images. |
| format | Article |
| id | doaj-art-8d9bfce2387a44e495d2b7c20966bd2d |
| institution | DOAJ |
| issn | 2644-125X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of the Communications Society |
| spelling | doaj-art-8d9bfce2387a44e495d2b7c20966bd2d2025-08-20T03:18:13ZengIEEEIEEE Open Journal of the Communications Society2644-125X2025-01-01618119710.1109/OJCOMS.2024.352135910811966Wavefield Networked Sensing: Principles, Algorithms, and ApplicationsMarco Manzoni0https://orcid.org/0000-0002-5525-0491Dario Tagliaferri1https://orcid.org/0000-0002-5718-4571Stefano Tebaldini2https://orcid.org/0000-0002-1229-3811Marouan Mizmizi3https://orcid.org/0000-0003-4157-2577Andrea Virgilio Monti-Guarnieri4https://orcid.org/0000-0003-2142-7807Claudio Maria Prati5https://orcid.org/0000-0001-5379-5634Umberto Spagnolini6https://orcid.org/0000-0002-7047-2455Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyNetworked sensing refers to the capability of multiple wireless terminals to cooperate with the aim of enhancing specific figures of merit, e.g., positioning accuracy or imaging resolution. Regarding radio-based sensing, it is essential to understand when and how sensing terminals should cooperate, namely the best strategy that trades between performance and cost (e.g., energy consumption, communication overhead, and complexity). This tutorial paper revises networked sensing from a wavefield interaction perspective, aiming to provide a general theoretical benchmark to evaluate its imaging performance bounds and to guide the sensing cooperation accordingly. Diffraction tomography theory (DTT) is the method to quantify the imaging resolution of any radio sensing experiment from inspection of its spectral (or wavenumber) content. In networked sensing, the image formation is based on the back-projection integral, valid for any network topology and physical configuration of the terminals. The wavefield networked sensing is a framework in which multiple sensing terminals cooperate during the acquisition process to maximize the imaging quality (resolution and sidelobes suppression) by pursuing the wavenumber tessellation principle. We discuss all the coherent data fusion possibilities between sensing terminals and possible killer applications. Remarkably, we show the possibility that the proposed method allows obtaining high-quality images of the environment in limited bandwidth conditions, leveraging the coherent combination of multiple multi-static low-resolution images.https://ieeexplore.ieee.org/document/10811966/Networked sensingdiffraction tomography theoryimagingcooperation |
| spellingShingle | Marco Manzoni Dario Tagliaferri Stefano Tebaldini Marouan Mizmizi Andrea Virgilio Monti-Guarnieri Claudio Maria Prati Umberto Spagnolini Wavefield Networked Sensing: Principles, Algorithms, and Applications IEEE Open Journal of the Communications Society Networked sensing diffraction tomography theory imaging cooperation |
| title | Wavefield Networked Sensing: Principles, Algorithms, and Applications |
| title_full | Wavefield Networked Sensing: Principles, Algorithms, and Applications |
| title_fullStr | Wavefield Networked Sensing: Principles, Algorithms, and Applications |
| title_full_unstemmed | Wavefield Networked Sensing: Principles, Algorithms, and Applications |
| title_short | Wavefield Networked Sensing: Principles, Algorithms, and Applications |
| title_sort | wavefield networked sensing principles algorithms and applications |
| topic | Networked sensing diffraction tomography theory imaging cooperation |
| url | https://ieeexplore.ieee.org/document/10811966/ |
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