Adaptive beamforming with joint robustness against signal mismatch and interference nonstationarity

Adaptive beamforming methods degrade in the presence of both signal mismatch and interference nonstationarity. This paper presents a more robust method to adaptive beamforming that provides joint robustness against signal mismatch and interference nonstationarity. We generalize the conventional linearly constrained minimum variance cost function by introducing the error matrix of signal covariance matrix and error constraints of DOA. The final cost function adopts the form of a support vector machine (SVM) for regression. Computer simulations demonstrate an improved performance in comparison with other robust beamforming techniques.