This letter deals with the problem of robust beamforming in the presence of non-Gaussian impulsive noise. Under this framework, a new robust extension of the empirical MVDR beamformer is developed. The proposed extension is a plug-in estimate of a measure-transformed MVDR (MT-MVDR) beamformer, that operates by applying a transform to the probability distribution of the data. The considered transform is generated by a non-negative data-weighting function, called MT-function. We show that proper selection of the MT-function can result in significantly enhanced beamforming performance in the presence of impulsive noise, while maintaining the implementation simplicity of the empirical MVDR. The proposed beamformer is evaluated in simulation studies that illustrate its advantages as compared to the empirical MVDR and other robust alternatives.

中文翻译：

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测量转换的 MVDR 波束成形

这封信涉及在存在非高斯脉冲噪声的情况下的鲁棒波束成形问题。在此框架下，开发了经验 MVDR 波束形成器的新的稳健扩展。提议的扩展是对测量转换的 MVDR (MT-MVDR) 波束成形器的插件估计，它通过对数据的概率分布应用变换来操作。所考虑的变换由非负数据加权函数生成，称为 MT 函数。我们表明，在存在脉冲噪声的情况下，正确选择 MT 函数可以显着增强波束成形性能，同时保持经验 MVDR 的实现简单性。所提出的波束成形器在模拟研究中进行了评估，与经验 MVDR 和其他稳健的替代方案相比，该研究说明了其优势。