RIS-Aided Sensing: Experimental Validation of Radar 3D Imaging in the mmWave Band
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866908962457124864 |
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| author | Micó-Rosa, Sergio Villaescusa-Tebar, Alvaro Fenollosa, Saúl Villena-Jiménez, Carlos Drozdowska, Monika Cardona, Narcis |
| author_facet | Micó-Rosa, Sergio Villaescusa-Tebar, Alvaro Fenollosa, Saúl Villena-Jiménez, Carlos Drozdowska, Monika Cardona, Narcis |
| contents | The transition toward 6G networks demands energy-efficient hardware capable of active interaction with the environment. Reconfigurable Intelligent Surfaces (RIS) have emerged as a key technology for Integrated Sensing and Communications (ISAC), enabling geometric environment recognition with minimal power consumption. However, achieving targeted 3D spatial mapping in a fully autonomous, closed-loop system remains a significant challenge. In this work, we validate experimentally an autonomous mmWave 3D imaging framework that integrates an Frequency-Modulated Continuous Wave (FMCW) radar with a 1-bit RIS and a Vector Network Analyzer (VNA) to perform targeted 3D reconstruction. The FMCW radar acts as a coarse localizer, providing real-time spatial priors to define dynamic Regions of Interest (ROI). These coordinates are translated into optimized RIS phase profiles to perform Stepped-Frequency Continuous-Wave (SFCW) measurements. We experimentally validate the system through three diverse scenarios, including metallic mannequins, calibration spheres, and a complex multi-target environment containing human subjects and an Automated Guided Vehicle (AGV). The results demonstrate accurate 3D voxel-based reconstruction of targets even at reduced angular resolutions, advancing the feasibility of RIS-based sensing for industrial and security applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_12466 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | RIS-Aided Sensing: Experimental Validation of Radar 3D Imaging in the mmWave Band Micó-Rosa, Sergio Villaescusa-Tebar, Alvaro Fenollosa, Saúl Villena-Jiménez, Carlos Drozdowska, Monika Cardona, Narcis Signal Processing The transition toward 6G networks demands energy-efficient hardware capable of active interaction with the environment. Reconfigurable Intelligent Surfaces (RIS) have emerged as a key technology for Integrated Sensing and Communications (ISAC), enabling geometric environment recognition with minimal power consumption. However, achieving targeted 3D spatial mapping in a fully autonomous, closed-loop system remains a significant challenge. In this work, we validate experimentally an autonomous mmWave 3D imaging framework that integrates an Frequency-Modulated Continuous Wave (FMCW) radar with a 1-bit RIS and a Vector Network Analyzer (VNA) to perform targeted 3D reconstruction. The FMCW radar acts as a coarse localizer, providing real-time spatial priors to define dynamic Regions of Interest (ROI). These coordinates are translated into optimized RIS phase profiles to perform Stepped-Frequency Continuous-Wave (SFCW) measurements. We experimentally validate the system through three diverse scenarios, including metallic mannequins, calibration spheres, and a complex multi-target environment containing human subjects and an Automated Guided Vehicle (AGV). The results demonstrate accurate 3D voxel-based reconstruction of targets even at reduced angular resolutions, advancing the feasibility of RIS-based sensing for industrial and security applications. |
| title | RIS-Aided Sensing: Experimental Validation of Radar 3D Imaging in the mmWave Band |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2604.12466 |