Autoregressive Power Spectrum-Based Covariance Matrix Reconstruction for Robust Adaptive Beamforming

In this paper, a new robust adaptive beamforming method based on the autoregressive (AR) power spectrum is proposed. To improve the robustness of the Capon spectrum, the AR model is applied to realize the desired signal power and interference power estimations, which are used to reconstruct the covariance matrix. Besides, the eigenvalue decomposition is used to remove the redundancy of the reconstructed interference-plus-noise covariance matrix, where the number of interferences is confirmed by the maximum ratio index of the adjacent eigenvalues. Numerical simulations highlight that the proposed method is more robust against some common errors compared with several beamformers.