Cooperative Localization and Multitarget Tracking in Agent Networks with the Sum-Product Algorithm
This paper addresses the problem of multitarget tracking using a network of sensing agents with unknown positions. Agents have to both localize themselves in the sensor network and, at the same time, perform multitarget tracking in the presence of clutter and miss detection. These two problems are j...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Open Journal of Signal Processing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9729221/ |
| _version_ | 1818126494928470016 |
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| author | Mattia Brambilla Domenico Gaglione Giovanni Soldi Rico Mendrzik Gabriele Ferri Kevin D. LePage Monica Nicoli Peter Willett Paolo Braca Moe Z. Win |
| author_facet | Mattia Brambilla Domenico Gaglione Giovanni Soldi Rico Mendrzik Gabriele Ferri Kevin D. LePage Monica Nicoli Peter Willett Paolo Braca Moe Z. Win |
| author_sort | Mattia Brambilla |
| collection | DOAJ |
| description | This paper addresses the problem of multitarget tracking using a network of sensing agents with unknown positions. Agents have to both localize themselves in the sensor network and, at the same time, perform multitarget tracking in the presence of clutter and miss detection. These two problems are jointly resolved using a holistic and centralized approach where graph theory is used to describe the statistical relationships among agent states, target states, and observations. A scalable message passing scheme, based on the sum-product algorithm, enables to efficiently approximate the marginal posterior distributions of both agent and target states. The proposed method is general enough to accommodate a full multistatic network configuration, with multiple transmitters and receivers. Numerical simulations show superior performance of the proposed joint approach with respect to the case in which cooperative self-localization and multitarget tracking are performed separately, as the former manages to extract valuable information from targets. Lastly, data acquired in 2018 by the NATO Science and Technology Organization (STO) Centre for Maritime Research and Experimentation (CMRE) through a network of autonomous underwater vehicles demonstrates the effectiveness of the approach in a practical application. |
| first_indexed | 2024-12-11T07:02:22Z |
| format | Article |
| id | doaj.art-18bb01c9b50145bb90ccf20a52798af1 |
| institution | Directory Open Access Journal |
| issn | 2644-1322 |
| language | English |
| last_indexed | 2024-12-11T07:02:22Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Signal Processing |
| spelling | doaj.art-18bb01c9b50145bb90ccf20a52798af12022-12-22T01:16:36ZengIEEEIEEE Open Journal of Signal Processing2644-13222022-01-01316919510.1109/OJSP.2022.31546849729221Cooperative Localization and Multitarget Tracking in Agent Networks with the Sum-Product AlgorithmMattia Brambilla0https://orcid.org/0000-0001-5442-6507Domenico Gaglione1https://orcid.org/0000-0001-7401-1659Giovanni Soldi2https://orcid.org/0000-0003-4426-7850Rico Mendrzik3https://orcid.org/0000-0002-5389-7945Gabriele Ferri4https://orcid.org/0000-0001-8830-193XKevin D. LePage5https://orcid.org/0000-0002-9311-2516Monica Nicoli6https://orcid.org/0000-0001-7104-7015Peter Willett7https://orcid.org/0000-0001-8443-5586Paolo Braca8https://orcid.org/0000-0002-3762-4373Moe Z. Win9https://orcid.org/0000-0002-8573-0488Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, ItalyNATO STO Centre for Maritime Research and Experimentation (CMRE), La Spezia, ItalyNATO STO Centre for Maritime Research and Experimentation (CMRE), La Spezia, ItalyIbeo Automotive Systems GmbH, Hamburg, GermanyNATO STO Centre for Maritime Research and Experimentation (CMRE), La Spezia, ItalyNATO STO Centre for Maritime Research and Experimentation (CMRE), La Spezia, ItalyDipartimento di Ingegneria Gestionale (DIG), Politecnico di Milano, Milan, ItalyUniversity of Connecticut, Storrs, CT, USANATO STO Centre for Maritime Research and Experimentation (CMRE), La Spezia, ItalyLaboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology (MIT), Cambridge, MA, USAThis paper addresses the problem of multitarget tracking using a network of sensing agents with unknown positions. Agents have to both localize themselves in the sensor network and, at the same time, perform multitarget tracking in the presence of clutter and miss detection. These two problems are jointly resolved using a holistic and centralized approach where graph theory is used to describe the statistical relationships among agent states, target states, and observations. A scalable message passing scheme, based on the sum-product algorithm, enables to efficiently approximate the marginal posterior distributions of both agent and target states. The proposed method is general enough to accommodate a full multistatic network configuration, with multiple transmitters and receivers. Numerical simulations show superior performance of the proposed joint approach with respect to the case in which cooperative self-localization and multitarget tracking are performed separately, as the former manages to extract valuable information from targets. Lastly, data acquired in 2018 by the NATO Science and Technology Organization (STO) Centre for Maritime Research and Experimentation (CMRE) through a network of autonomous underwater vehicles demonstrates the effectiveness of the approach in a practical application.https://ieeexplore.ieee.org/document/9729221/Belief propagationfactor graphmaritime surveillancemessage passingprobabilistic data association |
| spellingShingle | Mattia Brambilla Domenico Gaglione Giovanni Soldi Rico Mendrzik Gabriele Ferri Kevin D. LePage Monica Nicoli Peter Willett Paolo Braca Moe Z. Win Cooperative Localization and Multitarget Tracking in Agent Networks with the Sum-Product Algorithm IEEE Open Journal of Signal Processing Belief propagation factor graph maritime surveillance message passing probabilistic data association |
| title | Cooperative Localization and Multitarget Tracking in Agent Networks with the Sum-Product Algorithm |
| title_full | Cooperative Localization and Multitarget Tracking in Agent Networks with the Sum-Product Algorithm |
| title_fullStr | Cooperative Localization and Multitarget Tracking in Agent Networks with the Sum-Product Algorithm |
| title_full_unstemmed | Cooperative Localization and Multitarget Tracking in Agent Networks with the Sum-Product Algorithm |
| title_short | Cooperative Localization and Multitarget Tracking in Agent Networks with the Sum-Product Algorithm |
| title_sort | cooperative localization and multitarget tracking in agent networks with the sum product algorithm |
| topic | Belief propagation factor graph maritime surveillance message passing probabilistic data association |
| url | https://ieeexplore.ieee.org/document/9729221/ |
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