Reconfigurable Intelligent Surfaces-assisted Positioning in Integrated Sensing and Communication Systems
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866912906652680192 |
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| author | Ta, Huyen-Trang Duong, Ngoc-Son Nguyen, Trung-Hieu Nguyen, Van-Linh Dinh, Thai-Mai |
| author_facet | Ta, Huyen-Trang Duong, Ngoc-Son Nguyen, Trung-Hieu Nguyen, Van-Linh Dinh, Thai-Mai |
| contents | This paper investigates the problem of high-precision target localization in integrated sensing and communication (ISAC) systems, where the target is sensed via both a direct path and a reconfigurable intelligent surface (RIS)-assisted reflection path. We first develop a sequential matched-filter estimator to acquire coarse angular parameters, followed by a range recovery process based on subcarrier phase differences. Subsequently, we formulate the target localization problem as a non-linear least squares optimization, using the coarse estimates to initialize the target's position coordinates. To solve this efficiently, we introduce a fast iterative refinement algorithm tailored for RIS-aided ISAC environments. Recognizing that the signal model involves both linear path gains and non-linear geometric dependencies, we exploit the separable least-squares structure to decouple these parameters. Furthermore, we propose a modified Levenberg algorithm with an approximation strategy, which enables low-cost parameter updates without necessitating repeated evaluations of the full non-linear model. Simulation results show that the proposed refinement method achieves accuracy comparable to conventional approaches, while significantly reducing algorithmic complexity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_14415 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Reconfigurable Intelligent Surfaces-assisted Positioning in Integrated Sensing and Communication Systems Ta, Huyen-Trang Duong, Ngoc-Son Nguyen, Trung-Hieu Nguyen, Van-Linh Dinh, Thai-Mai Signal Processing Information Theory This paper investigates the problem of high-precision target localization in integrated sensing and communication (ISAC) systems, where the target is sensed via both a direct path and a reconfigurable intelligent surface (RIS)-assisted reflection path. We first develop a sequential matched-filter estimator to acquire coarse angular parameters, followed by a range recovery process based on subcarrier phase differences. Subsequently, we formulate the target localization problem as a non-linear least squares optimization, using the coarse estimates to initialize the target's position coordinates. To solve this efficiently, we introduce a fast iterative refinement algorithm tailored for RIS-aided ISAC environments. Recognizing that the signal model involves both linear path gains and non-linear geometric dependencies, we exploit the separable least-squares structure to decouple these parameters. Furthermore, we propose a modified Levenberg algorithm with an approximation strategy, which enables low-cost parameter updates without necessitating repeated evaluations of the full non-linear model. Simulation results show that the proposed refinement method achieves accuracy comparable to conventional approaches, while significantly reducing algorithmic complexity. |
| title | Reconfigurable Intelligent Surfaces-assisted Positioning in Integrated Sensing and Communication Systems |
| topic | Signal Processing Information Theory |
| url | https://arxiv.org/abs/2602.14415 |