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An ADMM-Based Approach to Robust Array Pattern Synthesis

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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… Click to show full abstract

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: synthesis; pattern synthesis; admm based; robust array; based approach

Journal Title: IEEE Signal Processing Letters
Year Published: 2019

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