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arXiv · 1901.06089

An ADMM-Based Approach to Robust Array Pattern Synthesis

Jintai Yang·Jingran Lin·Qingjiang Shi·Qiang Li
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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. Based on this model, we formulate the robust array 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 non-convex constraints. As a remedy, we employ the worst-case criterion and recast the problem as a convex second-order cone program (SOCP). To solve the SOCP, we further develop an alternating direction method of multipliers (ADMM)-based algorithm, which is computationally efficient with each step being computed in closed form. Numerical simulations demonstrate the efficacy and efficiency of the proposed algorithm.

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Jintai Yang, Jingran Lin, Qingjiang Shi, Qiang Li. 2019-01-18. An ADMM-Based Approach to Robust Array Pattern Synthesis. https://doi.org/10.1109/lsp.2019.2912456

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