Robust adaptive beamforming with positive semi-definite constraint using single variable minimization

Suraj Patil, V. Nagrale
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Abstract

In this paper, we propose a new method to solve the robust adaptive beamforming problem for the general rank signal model with positive semi-definite constraint. On applying the worst-case performance optimization approach, the considered robust adaptive beamforming problem generates a non-convex optimization problem. Here, we propose a two step closed form solution of the formulated problem, wherein a new single variable minimization problem is constructed. Result of this minimization is used to solve the robust adaptive beamforming problem. Simulation results verify the improvement in the performance by the proposed method over the current robust adaptive beamforming methods for general-rank signal model.
基于单变量最小化的正半确定约束鲁棒自适应波束形成
本文提出了一种新的方法来解决具有正半定约束的一般秩信号模型的鲁棒自适应波束形成问题。在应用最坏情况性能优化方法时,所考虑的鲁棒自适应波束形成问题产生一个非凸优化问题。在这里,我们提出了一个两步封闭解,其中构造了一个新的单变量最小化问题。该最小化结果用于解决鲁棒自适应波束形成问题。仿真结果验证了该方法比现有的一般秩信号模型鲁棒自适应波束形成方法的性能有所提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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