Dreamer: Dual-RIS-aided Imager in Complementary Modes
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arXiv
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| Auteurs principaux: | , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866913439231770624 |
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| author | Wang, Fuhai Huang, Yunlong Feng, Zhanbo Xiong, Rujing Li, Zhe Wang, Chun Mi, Tiebin Qiu, Robert Caiming Ling, Zenan |
| author_facet | Wang, Fuhai Huang, Yunlong Feng, Zhanbo Xiong, Rujing Li, Zhe Wang, Chun Mi, Tiebin Qiu, Robert Caiming Ling, Zenan |
| contents | Reconfigurable intelligent surfaces (RISs) have emerged as a promising auxiliary technology for radio frequency imaging. However, existing works face challenges of faint and intricate back-scattered waves and the restricted field-of-view (FoV), both resulting from complex target structures and a limited number of antennas. The synergistic benefits of multi-RIS-aided imaging hold promise for addressing these challenges. Here, we propose a dual-RIS-aided imaging system, Dreamer, which operates collaboratively in complementary modes (reflection-mode and transmission-mode). Dreamer significantly expands the FoV and enhances perception by deploying dual-RIS across various spatial and measurement patterns. Specifically, we perform a fine-grained analysis of how radio-frequency (RF) signals encode scene information in the scattered object modeling. Based on this modeling, we design illumination strategies to balance spatial resolution and observation scale, and implement a prototype system in a typical indoor environment. Moreover, we design a novel artificial neural network with a CNN-external-attention mechanism to translate RF signals into high-resolution images of human contours. Our approach achieves an impressive SSIM score exceeding 0.83, validating its effectiveness in broadening perception modes and enhancing imaging capabilities. The code to reproduce our results is available at https://github.com/fuhaiwang/Dreamer. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_14820 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Dreamer: Dual-RIS-aided Imager in Complementary Modes Wang, Fuhai Huang, Yunlong Feng, Zhanbo Xiong, Rujing Li, Zhe Wang, Chun Mi, Tiebin Qiu, Robert Caiming Ling, Zenan Signal Processing Reconfigurable intelligent surfaces (RISs) have emerged as a promising auxiliary technology for radio frequency imaging. However, existing works face challenges of faint and intricate back-scattered waves and the restricted field-of-view (FoV), both resulting from complex target structures and a limited number of antennas. The synergistic benefits of multi-RIS-aided imaging hold promise for addressing these challenges. Here, we propose a dual-RIS-aided imaging system, Dreamer, which operates collaboratively in complementary modes (reflection-mode and transmission-mode). Dreamer significantly expands the FoV and enhances perception by deploying dual-RIS across various spatial and measurement patterns. Specifically, we perform a fine-grained analysis of how radio-frequency (RF) signals encode scene information in the scattered object modeling. Based on this modeling, we design illumination strategies to balance spatial resolution and observation scale, and implement a prototype system in a typical indoor environment. Moreover, we design a novel artificial neural network with a CNN-external-attention mechanism to translate RF signals into high-resolution images of human contours. Our approach achieves an impressive SSIM score exceeding 0.83, validating its effectiveness in broadening perception modes and enhancing imaging capabilities. The code to reproduce our results is available at https://github.com/fuhaiwang/Dreamer. |
| title | Dreamer: Dual-RIS-aided Imager in Complementary Modes |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2407.14820 |