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Rectification of cross spectral matrices for arrays of arbitrary geometry

机译:校正任意几何阵列的交叉谱矩阵

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In high resolution methods applied to uniform linear arrays (ULA), the pre-processing that consists in forcing the estimated cross spectral matrix (CSM) to be Toeplitz by averaging its elements along its diagonals is known to increase drastically the resolving power: that is why it is always done in practice. However, this approach is limited to linear arrays because of the required Toeplitz structure for the CSM. This paper generalizes this technique to arrays of arbitrary geometry: the developed method is referred to as rectification. It proceeds by searching first for a vector subspace of Hermitian matrices that contains the manifold generated by the CSMs when the angle of arrival varies: this preliminary step is performed only one time for a given array geometry. Next, rectification of estimated CSMs is achieved by projecting them onto this subspace, resulting in denoising and increased resolving power of source localization methods at a very low computational cost. As a by product, the storage requirements for the CSMs are greatly reduced.
机译:在应用于均匀线性阵列(ULA)的高分辨率方法中,通过对沿其对角线方向的元素求平均来强制将估计的交叉光谱矩阵(CSM)设为Toeplitz的预处理会极大地提高分辨能力:为什么总是在实践中做到这一点。但是,由于CSM需要使用Toeplitz结构,因此该方法仅限于线性阵列。本文将这种技术推广到任意几何形状的阵列:所开发的方法称为“校正”。它首先搜索Hermitian矩阵的向量子空间,该向量子空间包含到达角变化时CSM生成的流形:对于给定的阵列几何形状,此预备步骤仅执行一次。接下来,通过将估计的CSM投影到该子空间上来进行校正,从而以非常低的计算成本实现了降噪并提高了源定位方法的分辨能力。作为副产品,CSM的存储需求大大降低了。

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