50 / 2019-12-10 12:48:00

A Low Complexity Algorithm for Mutual Coupling Coefficients Estimation

Mutual coupling; uniform linear array; parameter estimation; subspace theory

Here a low complexity subspace-based algorithm for estimating mutual coupling coefficients is proposed. Since mutual coupling matrix can be molded as a banded symmetric Toeplitz matrix for a uniform linear array, a novel transformation is constructed. Based on the transformation matrix and the subspace theory, transitional matrices corresponding to different signals are constructed, and the mutual coupling coefficients vector is estimated by eigen-decomposing the transitional matrices. In view of the large difference of signal-to-noise ratio (SNR) between different signals, the proposed method is modified. The estimation of the mutual coupling coefficients corresponding to the signal with the highest power is used as the final estimate to improve the estimation accuracy of the mutual coupling coefficients in the presence of the signals with different SNR. Simulation results demonstrate the validity of the proposed method.