Optimal flow models for multiscan data association
Multiscan data association can significantly enhance tracking performance in critical radar surveillance scenarios involving multiple targets, low detection probability, high false alarm probability, evasive target maneuvers, and finite radar resolution. Unfortunately, however, this approach is affe...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
| Published: |
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/44012 |
| _version_ | 1848756876124094464 |
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| author | Battistelli, G. Chisci, L. Papi, Francesco Benavoli, A. Farina, A. Graziano, A. |
| author_facet | Battistelli, G. Chisci, L. Papi, Francesco Benavoli, A. Farina, A. Graziano, A. |
| author_sort | Battistelli, G. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Multiscan data association can significantly enhance tracking performance in critical radar surveillance scenarios involving multiple targets, low detection probability, high false alarm probability, evasive target maneuvers, and finite radar resolution. Unfortunately, however, this approach is affected by the curse of dimensionality which hinders its real-time application for tracking problems with short scan periods and/or a high number of scans of the association logics and/or many measurements per scan. It is shown here how the formulation of the multiscan association as a multi-commodity or single-commodity flow optimization problem allows a relaxation of the association problem which, on one hand, provides close-to-optimal association performance and, on the other hand, implies a significant reduction of the computational load. © 2011 IEEE. |
| first_indexed | 2025-11-14T09:19:09Z |
| format | Journal Article |
| id | curtin-20.500.11937-44012 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:19:09Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-440122017-09-13T14:04:52Z Optimal flow models for multiscan data association Battistelli, G. Chisci, L. Papi, Francesco Benavoli, A. Farina, A. Graziano, A. Multiscan data association can significantly enhance tracking performance in critical radar surveillance scenarios involving multiple targets, low detection probability, high false alarm probability, evasive target maneuvers, and finite radar resolution. Unfortunately, however, this approach is affected by the curse of dimensionality which hinders its real-time application for tracking problems with short scan periods and/or a high number of scans of the association logics and/or many measurements per scan. It is shown here how the formulation of the multiscan association as a multi-commodity or single-commodity flow optimization problem allows a relaxation of the association problem which, on one hand, provides close-to-optimal association performance and, on the other hand, implies a significant reduction of the computational load. © 2011 IEEE. 2011 Journal Article http://hdl.handle.net/20.500.11937/44012 10.1109/TAES.2011.6034641 restricted |
| spellingShingle | Battistelli, G. Chisci, L. Papi, Francesco Benavoli, A. Farina, A. Graziano, A. Optimal flow models for multiscan data association |
| title | Optimal flow models for multiscan data association |
| title_full | Optimal flow models for multiscan data association |
| title_fullStr | Optimal flow models for multiscan data association |
| title_full_unstemmed | Optimal flow models for multiscan data association |
| title_short | Optimal flow models for multiscan data association |
| title_sort | optimal flow models for multiscan data association |
| url | http://hdl.handle.net/20.500.11937/44012 |