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Direction-of-arrival estimation based on spatial-temporal statistics without knowing the source number

机译:在不知道源编号的情况下,基于时空统计的到达方向估计

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Direction-of-arrival (DOA) estimation is a central problem in array processing and has a variety of applications. In this paper, a new algorithm for finding DOAs of multiple temporally correlated signals is devised. The proposed approach is based on the joint diagonalization structure of a set of spatio-temporal correlation matrices. Unlike the subspace-based DOA estimators, it is not necessary to estimate the noise or signal subspace explicitly. Moreover, the proposed method can provide the spatial spectrum and estimate the DOAs even when the number of sources is not known a priori. Interestingly, it is revealed that the well-known MUSIC method is a special case of our algorithm. Simulation results validate that the developed approach is superior to conventional DOA estimators in terms of resolution capability, estimation accuracy, and robustness against array model errors.
机译:到达方向(DOA)估计是阵列处理中的核心问题,具有多种应用。本文提出了一种寻找多个时间相关信号DOA的新算法。所提出的方法基于一组时空相关矩阵的联合对角化结构。与基于子空间的DOA估计器不同,无需显式估计噪声或信号子空间。此外,即使在先验未知源数量的情况下,所提出的方法也可以提供空间频谱并估计DOA。有趣的是,它揭示了众所周知的MUSIC方法是我们算法的特例。仿真结果证明,该方法在分辨率,估计精度和针对阵列模型错误的鲁棒性方面均优于传统的DOA估计器。

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