When a small number of snapshots are used, the performance of the direction-of-arrival (DOA) estimation method based on the least squares (LS) degrades severely because of inadequate estimation of the covariance matrix. Although the subspace-based DOA estimation methods were proposed to improve the performance of DOA estimation method based on the LS; however these methods are computationally complex, especially for a large number of array elements. In this Letter, the DOA estimation method based on the LS is improved by reconstructing the covariance matrix with diagonal loading, where the diagonal loading factor is computed automatically by estimating the signal power. The reciprocal of the array pattern is taken to calculate the spatial spectrum, where the peak values correspond to the estimated DOAs of signals. The proposed method can achieve better performance with few snapshots and low computational complexity. The effectiveness of the proposed method is verified by the numerical simulations.

中文翻译：

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自动对角线加载重建协方差矩阵的基于最小二乘的到达方向估计方法

当使用少量快照时，由于协方差矩阵的估计不足，因此基于最小二乘（LS）的到达方向（DOA）估计方法的性能会严重下降。尽管提出了基于子空间的DOA估计方法以提高基于LS的DOA估计方法的性能，但是，但是，这些方法计算复杂，尤其是对于大量数组元素而言。在这封信中，通过重建带有对角线负载的协方差矩阵改进了基于LS的DOA估计方法，其中通过估计信号功率自动计算对角线负载因子。阵列图案的倒数用于计算空间频谱，其中峰值对应于信号的估计DOA。所提出的方法可以以较少的快照和较低的计算复杂度实现更好的性能。数值仿真验证了该方法的有效性。