Adaptive beamforming with joint robustness against signal steering vector errors and interference nonstationarity

Adaptive beamforming methods are known to degrade in the presence of both signal steering vector errors and interference nonstationarity. In this paper, we develop a new approach to adaptive beamforming which is jointly robust against these two phenomena. Our approach is based on the optimization of the worst-case beamforming performance. A computationally efficient convex optimization based algorithm is proposed to compute the beamformer weights. Computer simulations compare the performance of our algorithm with other robust adaptive beamforming techniques.

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