基于协方差矩阵稀疏重构的协方差阵Doa估计

Chengwei Zhou, Zhiguo Shi, Yujie Gu, N. Goodman
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引用次数: 35

摘要

本文提出了一种基于协方差矩阵稀疏重构的协方差矩阵到达方向估计方法。具体来说,通过求解一个新制定的凸优化问题来估计源位置,其中空间平滑协方差矩阵与稀疏重构矩阵之间的差最小。然后,设计了一种用于源枚举的滑动窗口方案。最后,将每个源的功率作为最小二乘问题重新估计。与现有方法相比,该方法充分利用了素数阵列增加的自由度,实现了更精确的源定位和功率估计性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Doa estimation by covariance matrix sparse reconstruction of coprime array
In this paper, we propose a direction-of-arrival estimation method by covariance matrix sparse reconstruction of coprime array. Specifically, source locations are estimated by solving a newly formulated convex optimization problem, where the difference between the spatially smoothed covariance matrix and the sparsely reconstructed one is minimized. Then, a sliding window scheme is designed for source enumeration. Finally, the power of each source is re-estimated as a least squares problem. Compared with existing methods, the proposed method achieves more accurate source localization and power estimation performance with full utilization of increased degrees of freedom provided by coprime array.
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