Automatic Generalized Loading for Robust Adaptive Beamforming

The goal of this letter is to derive robust adaptive beamformers via generalized loading. In the proposed methods, Hermitian matrices are loaded on sample covariance matrix, and this is different from those methods based on the well-known diagonal loading approach. Furthermore, the computation of the loaded matrix is fully automatic, which is scarce in the literature. Numerical examples show that our methods are more robust to errors on array steering vector and sample covariance matrix than other tested parameter-free methods.

[1]  Stephen P. Boyd,et al.  Robust minimum variance beamforming , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[2]  Jian Li,et al.  Fully Automatic Computation of Diagonal Loading Levels for Robust Adaptive Beamforming , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[3]  Zhi-Quan Luo,et al.  Robust adaptive beamforming for general-rank signal models , 2003, IEEE Trans. Signal Process..

[4]  Wei Li,et al.  Fully automatic robust adaptive beamforming via Principal Component Regression , 2008, 2008 9th International Conference on Signal Processing.

[5]  Jian Li,et al.  On Using a priori Knowledge in Space-Time Adaptive Processing , 2008, IEEE Transactions on Signal Processing.

[6]  Zhi-Quan Luo,et al.  Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem , 2003, IEEE Trans. Signal Process..

[7]  Yonina C. Eldar,et al.  Robust mean-squared error estimation in the presence of model uncertainties , 2005, IEEE Transactions on Signal Processing.

[8]  Petre Stoica,et al.  Automatic robust adaptive beamforming via ridge regression , 2008, Signal Process..

[9]  Wei Li,et al.  Robust adaptive beamforming using partial least squares , 2008, 2008 9th International Conference on Signal Processing.

[10]  Jian Li,et al.  On robust Capon beamforming and diagonal loading , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..