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Direction-of-Arrival Estimation of Wideband Signals via Covariance Matrix Sparse Representation

机译:协方差矩阵稀疏表示的宽带信号到达方向估计

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This paper focuses on direction-of-arrival (DOA) estimation of wideband signals, and a method named wideband covariance matrix sparse representation (W-CMSR) is proposed. In W-CMSR, the lower left triangular elements of the covariance matrix are aligned to form a new measurement vector, and DOA estimation is then realized by representing this vector on an over-complete dictionary under the constraint of sparsity. The a priori information of the incident signal number is not needed in W-CMSR, and no spectral decomposition or focusing is introduced. Simulation results demonstrate the satisfying performance of W-CMSR in wideband DOA estimation in various settings. Moreover, theoretical analysis and numerical examples show how many simultaneous signals can be separated by W-CMSR on typical array geometries, and that the half-wavelength spacing restriction in avoiding ambiguity can be relaxed from the highest to the lowest frequency of the incident wideband signals.
机译:本文着重研究宽带信号的到达方向(DOA)估计,提出了一种宽带协方差矩阵稀疏表示(W-CMSR)方法。在W-CMSR中,将协方差矩阵的左下三角元素对齐以形成一个新的测量向量,然后在稀疏性约束下,通过在一个过度完成的字典上表示该向量来实现DOA估计。 W-CMSR不需要入射信号号的先验信息,并且不引入频谱分解或聚焦。仿真结果证明了W-CMSR在各种设置下对宽带DOA估计的令人满意的性能。此外,理论分析和数值示例表明,在典型的阵列几何结构上,W-CMSR可以分离多少个同时出现的信号,并且可以避免入射宽带信号的最高频率到最低频率放宽避免模糊的半波长间隔限制。

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