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An extension of the MUSIC algorithm to broadband scenarios using a polynomial eigenvalue decomposition

机译:使用多项式特征值分解将MUSIC算法扩展到宽带场景

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The multiple signal classification (MUSIC) algorithm for direction of arrival estimation is defined for narrowband scenarios. In this paper, a generalisation to the broadband case is presented, based on a description of broadband systems by polynomial space-time covariance matrices. A polynomial eigenvalue decomposition is used to determine the noise-only subspace of the this matrix, which can be scanned by appropriately defined broadband steering vectors. Two broadband MUSIC algorithm versions are presented, which resolve either angle of arrival alone or in combination with the frequency range over which sources are active. Initial results for these approaches are presented and demonstrate a significant benefit over independent frequency bin processing using narrowband MUSIC.
机译:针对窄带场景定义了用于到达方向估计的多信号分类(MUSIC)算法。在本文中,基于多项式时空协方差矩阵对宽带系统的描述,给出了对宽带情况的概括。多项式特征值分解用于确定此矩阵的纯噪声子空间,可以通过适当定义的宽带导引向量对其进行扫描。给出了两种宽带MUSIC算法版本,它们可以单独解决到达角,也可以与源活动的频率范围结合解决。提出了这些方法的初步结果,并证明了它们优于使用窄带MUSIC的独立频率仓处理。

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