Towards ISAC RIS-Enabled Passive Radar Target Localization
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866910845645094912 |
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| author | Bazzi, Ahmad Chafii, Marwa |
| author_facet | Bazzi, Ahmad Chafii, Marwa |
| contents | Incorporating integrated sensing and communication capabilities into forthcoming 6G wireless networks is crucial for achieving seamless synchronization between the digital and physical worlds. The following paper focuses on a scenario where a passive radar (PR) is subject to weak line-of-sight signals of opportunity, emanating from an access point and subsequently reflecting off targets, ultimately reaching the PR. Furthermore, a normalized least mean squares method is presented for jointly detecting the number of targets and estimating target angles of arrival (AoAs). The algorithm iteratively adjusts the steering vector estimates to minimize a suitable error cost function, while the target AoAs are identified via a peak-finding search conducted on the resulted power spectrum. Simulation results show the capabilities of the proposed localization method, as well as a 14 dB dynamic range reduction that can be achieved at the PR. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2502_18787 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards ISAC RIS-Enabled Passive Radar Target Localization Bazzi, Ahmad Chafii, Marwa Signal Processing Incorporating integrated sensing and communication capabilities into forthcoming 6G wireless networks is crucial for achieving seamless synchronization between the digital and physical worlds. The following paper focuses on a scenario where a passive radar (PR) is subject to weak line-of-sight signals of opportunity, emanating from an access point and subsequently reflecting off targets, ultimately reaching the PR. Furthermore, a normalized least mean squares method is presented for jointly detecting the number of targets and estimating target angles of arrival (AoAs). The algorithm iteratively adjusts the steering vector estimates to minimize a suitable error cost function, while the target AoAs are identified via a peak-finding search conducted on the resulted power spectrum. Simulation results show the capabilities of the proposed localization method, as well as a 14 dB dynamic range reduction that can be achieved at the PR. |
| title | Towards ISAC RIS-Enabled Passive Radar Target Localization |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2502.18787 |