Multiscan association as a multi-commodity flow optimization problem
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 affec...
| Main Authors: | , , , , |
|---|---|
| Format: | Conference Paper |
| Published: |
2008
|
| Online Access: | http://hdl.handle.net/20.500.11937/39054 |
| _version_ | 1848755486291132416 |
|---|---|
| author | Battistelli, G. Chisci, L. Papi, Francesco Benavoli, A. Farina, A. |
| author_facet | Battistelli, G. Chisci, L. Papi, Francesco Benavoli, A. Farina, 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 long association windows and/or many measurements. In this paper it is shown how the formulation of the multiscan association as a multi-commodity flow optimization problem allows a relaxation of the association problem which, on one hand, guarantees close-to-optimal association performance and, on the other hand, implies a significant reduction of the computational load. © 2008 IEEE. |
| first_indexed | 2025-11-14T08:57:04Z |
| format | Conference Paper |
| id | curtin-20.500.11937-39054 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:57:04Z |
| publishDate | 2008 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-390542017-09-13T14:19:38Z Multiscan association as a multi-commodity flow optimization problem Battistelli, G. Chisci, L. Papi, Francesco Benavoli, A. Farina, 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 long association windows and/or many measurements. In this paper it is shown how the formulation of the multiscan association as a multi-commodity flow optimization problem allows a relaxation of the association problem which, on one hand, guarantees close-to-optimal association performance and, on the other hand, implies a significant reduction of the computational load. © 2008 IEEE. 2008 Conference Paper http://hdl.handle.net/20.500.11937/39054 10.1109/RADAR.2008.4721109 restricted |
| spellingShingle | Battistelli, G. Chisci, L. Papi, Francesco Benavoli, A. Farina, A. Multiscan association as a multi-commodity flow optimization problem |
| title | Multiscan association as a multi-commodity flow optimization problem |
| title_full | Multiscan association as a multi-commodity flow optimization problem |
| title_fullStr | Multiscan association as a multi-commodity flow optimization problem |
| title_full_unstemmed | Multiscan association as a multi-commodity flow optimization problem |
| title_short | Multiscan association as a multi-commodity flow optimization problem |
| title_sort | multiscan association as a multi-commodity flow optimization problem |
| url | http://hdl.handle.net/20.500.11937/39054 |