论文标题
基于实价奇异值分解的准确DOA估计
Accurate DOA Estimation Based on Real-Valued Singular Value Decomposition
论文作者
论文摘要
在本文中，根据协方差矩阵的实数奇异值分解（SVD），开发了准确的排序方向（DOA）估计器。首先应用了复杂值协方差矩阵上的统一变换，然后SVD在所得的实值数据矩阵上执行。然后，使用加权最小二乘（WLS）方法来利用单数矢量来实现DOA估计。将所提出的算法的性能与几种最新方法以及CRB进行了比较。结果表明该方法的准确性和有效性。
In this paper, an accurate direction-of-arrival (DOA) estimator is developed based on the real-valued singular value decomposition (SVD) of covariance matrix. Unitary transform on the complex-valued covariance matrix is first applied, and then SVD performs on the resulting real-valued data matrix. The singular vector is then utilized with a weighted least squares (WLS) method to achieve DOA estimation. The performance of the proposed algorithm is compared with several state-of-the-art methods as well as the CRB. The results indicate the accuracy and effectiveness of the proposed method.
