A Multi-RIS-Assisted Static Environment Sensing Method

Existing channel state information (CSI)-based environmental sensing methods face challenges related to high hardware costs and limited sensing capabilities for stationary environments. By utilizing the ability of reconfigurable intelligent surfaces (RIS) to modulate wireless signals rapidly, this letter proposes a multi-RIS-assisted static environmental sensing method to address these issues in limited hardware resource scenarios. Precisely, we model the environment as a point cloud, which is sensed by detecting the direction of the reflected signal at each point. Then, an atomic norm minimization (ANM)-based environment sensing algorithm is proposed to sense the distribution of points. Simulation results show that this method can achieve environmental sensing with an error margin of no more than 0.05 meters in a single-user, single-antenna scenario.