High-precision passive sensing with large-scale programmable metasurface

With the rapid development of sixth-generation (6G) intelligent wireless networks, environmental sensing has become a core requirement for many applications such as autonomous driving, drones, and intelligent robotics. Here, we propose a passive sensing method based on beam-focusing algorithms and a large-scale programmable metasurface composed of 64 × 96 effective elements. The coding patterns on the 1-bit programmable metasurface are dynamically switched via a field-programmable gate array (FPGA) to achieve real-time beam focusing and scanning at specific spatial locations. The reflected signal strength is then used to determine the target angle and distance. Requiring only a single RF channel and signal strength information, the system features a simple hardware architecture and low computational complexity. To verify the effectiveness and robustness of the proposed method, experiments are conducted across 74 positions within an azimuth-angle range from −70° to 70° and a distance range from 1 m to 3 m. The experimental results demonstrate that the proposed sensing method achieves high precision in both angle and distance for passive targets, with an average absolute angle error of 0.904° and an average absolute distance error of 0.101 m. The proposed system provides a promising solution for applications in the Internet of Things, directional communication, and biomedical fields.