Enhancing polynomial MUSIC algorithm for coherent broadband sources through spatial smoothing

William Coventry, C. Clemente, J. Soraghan
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引用次数: 9

Abstract

Direction of arrival algorithms which exploit the eigenstructure of the spatial covariance matrix (such as MUSIC) encounter difficulties in the presence of strongly correlated sources. Since the broadband polynomial MUSIC is an extension of the narrowband version, it is unsurprising that the same issues arise. In this paper, we extend the spatial smoothing technique to broadband scenarios via spatially averaging polynomial spacetime covariance matrices. This is shown to restore the rank of the polynomial source covariance matrix. In the application of the polynomial MUSIC algorithm, the spatially smoothed spacetime covariance matrix greatly enhances the direction of arrival estimate in the presence of strongly correlated sources. Simulation results are described shows the performance improvement gained using the new approach compared to the conventional non-smoothed method.
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通过空间平滑改进相干宽带源的多项式MUSIC算法
利用空间协方差矩阵特征结构的到达方向算法(如MUSIC)在存在强相关源时遇到困难。由于宽带多项式MUSIC是窄带版本的扩展,因此出现相同的问题并不奇怪。在本文中,我们通过空间平均多项式时空协方差矩阵将空间平滑技术扩展到宽带场景。这显示了恢复多项式源协方差矩阵的秩。在多项式MUSIC算法的应用中,空间平滑的时空协方差矩阵极大地增强了强相关源存在时的到达方向估计。仿真结果表明,与传统的非光滑方法相比,新方法的性能得到了提高。
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