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Robust adaptive beamforming with null-pattern constraints
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DOI：10.1016/j.sigpro.2019.107420.png)
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Robust adaptive beamforming (RAB) technique is designed to avoid self-cancelation in the presence of mismatch between the nominal and actual models. In this paper, we have made the following three main contributions: 1) we show that the ripple control over the steering vector uncertainty set can be transformed to a norm constraint for the weight vector, in which the maximum norm is a function of the radius of the steering vector uncertainty set, the wanted ripple level and the number of array sensors; 2) in order to maintain the interference suppression ability (particularly for the distributed interferences) we develop a new RAB in which null-pattern constraints are incorporated; 3) we prove that the weight-vector norm is a monotonically decreasing function of the loading factor. Simulation results are also provided to demonstrate the effectiveness of our proposed algorithms. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Robust adaptive beamforming (RAB)
Null-pattern constraint
Ripple control
Array signal processing
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