RIS-Enabled Multi-Target Sensing: Performance Analysis and Space-Time Beamforming Design

Recently, reconfigurable intelligent surface (RIS) has gained growing research interests in sensing fields. While extensive efforts have been devoted to designing RIS space beamforming for improving sensing accuracy, the potential of RIS in improving sensing resolution has so far not been fully dug. In this paper, we investigate the fundamental performance of RIS-enabled multi-target sensing, and exploit the potential of RIS in simultaneously boosting resolution and accuracy. Specifically, based on the identification that sensing is to obtain target state information from the received echo signals, we adopt the sensing mutual information as the performance metric, thus enabling comprehensive evaluation of both sensing resolution and accuracy. Then, we derive the analytical expression of the sensing mutual information in our considered systems, revealing that in addition to providing beamforming gains to enhance sensing accuracy in the space domain, RIS can also flexibly vary its beamforming in the time domain to improve sensing resolution. Based on this result, we propose a novel space-time beamforming, in which space-domain and time-domain beamforming gains are utilized for enhancing sensing accuracy and resolution, respectively. Numerical results demonstrate the significant advantages of the proposed space-time beamforming scheme over the traditional space-only beamforming scheme in terms of sensing resolution.