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Blind Co-Channel Source Separation in Sparse Interferometric Arrays

机译:稀疏干涉阵列中的盲同信道源分离

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Interferometric arrays used for radio astronomy and passive interception of RF signals typically use a calibration table to derive direction-of-arrival (DoA) information. But there are some applications, such as separation and identification of multiple source mixtures overlapping in frequency, which do not require DoA information. In those cases, blind source separation / blind beamforming techniques can be applied. Yet the irregular and sparse nature of typical interferometric arrays introduce issues with standard blind algorithms. In particular, traditional assumptions of signal independence and identifiability are sometimes invalid. In this paper, we examine the performance of the Joint Approximate Diagonalization of Eigen-matrices (JADE) blind source separation algorithm in the context of interferometric array processing. We show that while the array structure does introduce some degradation at certain directions-of-arrival, performance remains quite good even in angles where underlying partial ambiguities exist.
机译:用于射电天文学和射频信号的被动拦截的干涉仪阵列通常使用校准表来得出到达方向(DoA)信息。但是有一些应用,例如分离和识别频率重叠的多个源混合物,不需要DoA信息。在那些情况下,可以应用盲源分离/盲波束成形技术。然而,典型的干涉阵列的不规则和稀疏性质引入了标准盲算法的问题。特别地,信号独立性和可识别性的传统假设有时是无效的。在本文中,我们在干涉阵列处理的背景下研究了本征矩阵联合近似对角化(JADE)盲源分离算法的性能。我们表明,虽然阵列结构确实在某些到达方向上引入了一些退化,但即使在存在潜在的部分歧义的角度下,性能仍然相当不错。

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