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An ADMM-Based Approach to Robust Array Pattern Synthesis
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DOI：10.1109/LSP.2019.2912456.png)
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Abstract
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In most existing robust array beam pattern synthesis studies, the bounded-sphere model is used to describe the steering vector (SV) uncertainties. In this letter, instead of bounding the norm of SV perturbations as a whole, we explore the amplitude and phase perturbations of each SV element separately, thereby obtaining a tighter SV uncertainty model. On the basis of this model, we formulate the robust pattern synthesis problem from the perspective of the min-max optimization, which aims to minimize the maximum side lobe response, while preserving the main lobe response. However, this problem is difficult due to the infinitely many nonconvex constraints. As a compromise, we employ the worst-case criterion and recast the problem as a convex second-order cone program (SOCP). To solve the SOCP, we further design an alternating direction method of multipliers based algorithm, which is computationally efficient by coming up with closed-form solutions in each step.
Keywords:
Pattern synthesis
steering vector perturbation
min-max optimization
second-order cone program (SOCP)
alternating direction method of multipliers (ADMM)
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