Mutual coupling estimation method of metasurfaces system based on sparse Bayesian learning

The radar system based on metasurfces is a new technology that can realize single-channel imaging. However, for the coupling between metasurface elements in a single-channel system, there are no effective solution at present. In this paper, we focus on the estimation of the mutual coupling between the coding metasurface elements. First, this paper establishes a mathematical model of a single-channel system including coupling parameters. Then by assuming the prior distribution of the parameters, the Bayesian method is used to obtain the posterior probability distribution of the parameters, and the expectation maximization (EM) method is used to estimate the unknown parameters in the model. Finally, numerical experiments verify the effectiveness of the proposed method.