Computational Imaging With Holographic RIS: Sensing Principle and Pathloss Analysis

Realizing the wireless environmental sensing is another desired function of reconfigurable intelligent surface (RIS), in addition to enhancing the performance of wireless communication systems. In this paper, we design a holographic RIS-aided computational imaging system, which consists of a transmitter, a holographic RIS, a rectangular target and a receiver. Here, the target is composed of a series of discrete segments, each of which possesses a constant scattering density. The sensing task of the proposed system is to estimate the scattering densities of the target, which corresponds to the term computational imaging. The term holographic means that the RIS is modeled as a physically continuous surface with a physically continuous phase shift pattern, which can be approximately considered as having massive (possibly infinite) number of elements within a finite space. Both the RIS and the target are subject to the electromagnetic boundary conditions, whose scattered fields are computed by the equivalent current method and the physical equivalent. Based on the computed scattered fields of the target, we derive the pathloss of the proposed system. In order to perform the imaging, we alter the phase shift pattern of the RIS such that the main energy of its scattered fields is focused towards different segments of the target successively, which then produces multiple measurements of the scattering densities and simultaneously ensures a low pathloss. After all measurements are completed, the scattering densities of the target can be estimated with the observed measurement vector and the reconstructed sensing channel, i.e., the computational imaging is accomplished. Simulation results show that the proposed imaging strategy performs well if the system parameters are designed properly.