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

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4 Author(s)
Vorobyov, S.A. ; Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada ; Gershman, A.B. ; Zhi-Quan Luo ; Ning Ma

Adaptive beamforming methods degrade in the presence of both signal steering vector errors and interference nonstationarity. We develop a new approach to adaptive beamforming that is jointly robust against these two phenomena. Our beamformer is based on the optimization of the worst case performance. A computationally efficient convex optimization-based algorithm is proposed to compute the beamformer weights. Computer simulations demonstrate that our beamformer has an improved robustness as compared to other popular robust beamforming algorithms.

Published in:

Signal Processing Letters, IEEE  (Volume:11 ,  Issue: 2 )