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Space-time signal subspace estimation for wide-band acoustic arrays

机译:宽带声学阵列的时空信号子空间估计

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Acoustic array applications are generally characterized by very large signal bandwidth. Most existing wide-band direction of arrival (DOA) estimators are based on binning in the frequency domain, so that within each bin the signal model is considered approximately narrow-band. In this work the basic inconsistency of the commonly used binning is first shown. It is shown that the recent Space Time MUSIC (ST-MUSIC) method, which estimates a set of narrow-band signal subspaces directly from the space-time array covariance and combines them within a Weighted Subspace Fitting paradigm, can restore wide-band DOA estimation consistency in most scenarios, obtaining a large variance improvement at high signal to noise ratio (SNR). In addition, a refined ST-MUSIC subspace weighting is proposed to improve accuracy, especially at low SNR.
机译:声学阵列的应用通常具有很大的信号带宽。现有的大多数宽带到达方向(DOA)估计器都是基于频域中的合并,因此,在每个合并中,信号模型被认为是近似窄带的。在这项工作中,首先显示了常用装箱的基本矛盾之处。结果表明,最近的时空音乐(ST-MUSIC)方法直接从空时阵列协方差估计一组窄带信号子空间并将其组合在加权子空间拟合范式中,可以恢复宽带DOA。在大多数情况下估计一致性,在高信噪比(SNR)时获得较大的方差改善。此外,提出了一种改进的ST-MUSIC子空间加权,以提高准确性,尤其是在低SNR情况下。

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