Joint Target Acquisition and Refined Position Estimation in OFDM-based ISAC Networks
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911047913308160 |
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| author | Pucci, Lorenzo Giorgetti, Andrea |
| author_facet | Pucci, Lorenzo Giorgetti, Andrea |
| contents | This paper addresses joint target acquisition and position estimation in an OFDM-based integrated sensing and communication (ISAC) network with base station (BS) cooperation via a fusion center. A two-stage framework is proposed: in the first stage, each BS computes range-angle maps to detect targets and estimate coarse positions, exploiting spatial diversity. In the second stage, refined localization is performed using a cooperative maximum likelihood (ML) estimator over predefined regions of interest (RoIs) within a shared global reference frame. Numerical results demonstrate that the proposed approach not only improves detection performance through BS cooperation but also achieves centimeter-level localization accuracy, highlighting the effectiveness of the refined estimation technique. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_07081 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Joint Target Acquisition and Refined Position Estimation in OFDM-based ISAC Networks Pucci, Lorenzo Giorgetti, Andrea Signal Processing This paper addresses joint target acquisition and position estimation in an OFDM-based integrated sensing and communication (ISAC) network with base station (BS) cooperation via a fusion center. A two-stage framework is proposed: in the first stage, each BS computes range-angle maps to detect targets and estimate coarse positions, exploiting spatial diversity. In the second stage, refined localization is performed using a cooperative maximum likelihood (ML) estimator over predefined regions of interest (RoIs) within a shared global reference frame. Numerical results demonstrate that the proposed approach not only improves detection performance through BS cooperation but also achieves centimeter-level localization accuracy, highlighting the effectiveness of the refined estimation technique. |
| title | Joint Target Acquisition and Refined Position Estimation in OFDM-based ISAC Networks |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2507.07081 |