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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.18774 |
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| _version_ | 1866916964081860608 |
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| author | Xi, Feng Yang, Dehui |
| author_facet | Xi, Feng Yang, Dehui |
| contents | Reconfigurable intelligent surface (RIS)-aided localization in the radiating near-field requires range-aware spherical-wave models, which inherently couple angles and ranges and thus complicate accurate 3D positioning. Using the Fresnel approximation, we show that the RIS response can be expressed as the element-wise product of a 2D far-field steering vector and a range-dependent quadratic-phase chirp. By modeling these chirp components within a low-dimensional subspace, we reformulate the joint recovery of azimuth, elevation, and range under a 2D super-resolution framework, resulting in a 2D atomic norm minimization (2D-ANM) problem. Solving this via semi-definite programming (SDP) yields gridless azimuth-elevation estimation and high-accuracy range recovery. Simulations demonstrate accurate 3D localization and enhanced robustness of the proposed scheme, compared with subspace and compressive sensing methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_18774 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Two-Dimensional Super-Resolution Method for Reconfigurable Intelligent Surface-Assisted Near-Field Localization Xi, Feng Yang, Dehui Information Theory Reconfigurable intelligent surface (RIS)-aided localization in the radiating near-field requires range-aware spherical-wave models, which inherently couple angles and ranges and thus complicate accurate 3D positioning. Using the Fresnel approximation, we show that the RIS response can be expressed as the element-wise product of a 2D far-field steering vector and a range-dependent quadratic-phase chirp. By modeling these chirp components within a low-dimensional subspace, we reformulate the joint recovery of azimuth, elevation, and range under a 2D super-resolution framework, resulting in a 2D atomic norm minimization (2D-ANM) problem. Solving this via semi-definite programming (SDP) yields gridless azimuth-elevation estimation and high-accuracy range recovery. Simulations demonstrate accurate 3D localization and enhanced robustness of the proposed scheme, compared with subspace and compressive sensing methods. |
| title | A Two-Dimensional Super-Resolution Method for Reconfigurable Intelligent Surface-Assisted Near-Field Localization |
| topic | Information Theory |
| url | https://arxiv.org/abs/2509.18774 |