Reconfigurable intelligent surface (RIS) or intelligent reflecting surface
(IRS) has been an attractive technology for future wireless communication and
sensing systems. However, in the practical RIS, the mutual coupling effect
among RIS elements, the reflection phase shift, and amplitude errors will
degrade the RIS performance significantly. This paper investigates the
two-dimensional direction-of-arrival (DOA) estimation problem in the scenario
using a practical RIS. After formulating the system model with the mutual
coupling effect and the reflection phase/amplitude errors of the RIS, a novel
DNNDANM method is proposed for the DOA estimation by combining the deep neural
network (DNN) and the decoupling atomic norm minimization (DANM). The DNN step
reconstructs the received signal from the one with RIS impairments, and the
DANM step exploits the signal sparsity in the two-dimensional spatial domain.
Additionally, a semi-definite programming (SDP) method with low computational
complexity is proposed to solve the atomic minimization problem. Finally, both
simulation and prototype are carried out to show estimation performance, and
the proposed method outperforms the existing methods in the two-dimensional DOA
estimation with low complexity in the scenario with practical RIS.Comment: 11 pages, 12 figure