Robust Adaptive Beamforming Against Mutual Coupling Based on Mutual Coupling Coefficients Estimation

In an adaptive beamforming system, the mutual coupling effects among the array elements can seriously degrade the system performance. In this paper, we propose a robust adaptive beamforming algorithm using a uniform linear array (ULA) to mitigate the mutual coupling effects. The proposed algorithm is based on the fact that the mutual coupling matrix (MCM) of a ULA can be approximated as a banded symmetric Toeplitz matrix as the mutual coupling between two sensors is inversely related to their separation and is negligible for a few wavelengths away. By exploiting the structural characteristics of the MCM, a subspace-based method is used to estimate the mutual coupling coefficients of the ULA that yield a closed-form solution, and the MCM is further constructed. Then, the constructed MCM and array received data are used to reconstruct the interference-plus-noise covariance (INC) matrix. Finally, the robust adaptive beamformer is created through using the Capon principle and the reconstructed INC matrix. Unlike most of the existing algorithms, the proposed algorithm only requires prior knowledge of the array geometry. Simulation results indicate that our approach outperforms the compared algorithms in the presence of unknown mutual coupling and can achieve a performance close to the theoretical optimal value.