  Near field computational imaging has been recognized as a promising technique
for non-destructive and highly accurate detection of the target. Meanwhile,
reconfigurable intelligent surface (RIS) can flexibly control the scattered
electromagnetic (EM) fields for sensing the target and can thus help
computational imaging in the near field. In this paper, we propose a near-field
imaging scheme based on holograghic aperture RIS. Specifically, we first
establish an end-to-end EM propagation model from the perspective of Maxwell
equations. To mitigate the inherent ill conditioning of the inverse problem in
the imaging system, we design the EM field patterns as masks that help
translate the inverse problem into a forward problem. Next, we utilize RIS to
generate different virtual EM masks on the target surface and calculate the
cross-correlation between the mask patterns and the electric field strength at
the receiver. We then provide a RIS design scheme for virtual EM masks by
employing a regularization technique. The cross-range resolution of the
proposed method is analyzed based on the spatial spectrum of the generated
masks. Simulation results demonstrate that the proposed method can achieve
high-quality imaging. Moreover, the imaging quality can be improved by
generating more virtual EM masks, by increasing the signal-to-noise ratio (SNR)
at the receiver, or by placing the target closer to the RIS.
