Enhanced 1-bit Programmable Metasurface Failure Diagnosis via Hadamard Matrices

In this paper, the failure diagnosis performance of the 1-bit programmable metasurface is improved by using the Hadamard matrix. According to the compressive sensing (CS) theory, the accuracy of sparse signal recovery is impacted by the orthogonality of the measurement matrix. Thus, the Hadamard matrix is introduced to build up the measurement matrix for 1-bit programmable metasurface failure diagnosis. In order to verify the validity of the proposed method, the diagnostic performance is compared when random and Hadamard matrices are utilized to construct the measurement matrix. Simulation results show that the Hadamard matrix achieves lower reconstruction errors and leads to improved fault diagnosis performance.