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Direction-of-Arrival Estimation Using a Sparse Representation Based on Fourth-order Cumulant

机译:基于四阶累积量的稀疏表示的到达方向估计

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Sparse iterative covariance-based estimation (SPICE) method is a computational efficient sparse method for direction of arrival (DOA) estimation but has a poor performance in resolution and noise immunity. The high-order cumulant can extend the array aperture and reduce the Gaussian noise. Therefore, this paper proposed an improved SPICE based on fourth-order cumulant, which shares the same features of SPICE but has higher resolution and outperforms in low SNR case. Moreover, its computational cost is comparatively low by distilling the un-redundant data of uniform linear array. Simulations were conducted to validate and evaluate the proposed method.
机译:基于稀疏迭代协方差的估计(SPICE)方法是一种用于到达方向(DOA)估计的计算有效的稀疏方法,但在分辨率和抗噪性方面性能较差。高阶累积量可以扩展阵列孔径并降低高斯噪声。因此,本文提出了一种基于四阶累积量的改进型SPICE,它具有与SPICE相同的特征,但具有较高的分辨率,并且在低SNR情况下性能优于。此外,通过提取均匀线性阵列的非冗余数据,其计算成本相对较低。仿真进行了验证和评估所提出的方法。

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