| 基于矩阵奇异值分解的空间谱估计算法 |
| |
| 引用本文： | 万明坚,肖先赐.基于矩阵奇异值分解的空间谱估计算法[J].电子科技大学学报(社会科学版),1989(2). |
| |
| 作者姓名： | 万明坚 肖先赐 |
| |
| 作者单位： | 电子科技大学电子工程系
(万明坚)，电子科技大学电子工程系(肖先赐) |
| |
| 摘 要： | 本文提出了一种利用矩阵奇异值分解来作空间谱估计的方法,即对由天线阵获取的数据所构成的数据矩阵作奇异值分解、删除来自噪声的贡献的诸最小奇异值以改善信噪比,并利用噪声奇异向量和天线阵的方向向量正交的性质来计算空间谱。除了奇异值分解算法本身给计算稳定性带来好处外,本方法的谱估计性能和计算量均优于近几年来国外广泛关注的一种谱估计算法——MUSIC算法。本方法可用于高分辨的测向系统中。
|
| 关 键 词： | 谱估计 算法 奇异值分解 分辨率 阵列 测向 MUSIC算法 空间 |
A HIGH RESOLUTION SPATIAL SPECTRAL ESTIMATION METHOD BASED ON THE SVD OF A DATA MATRIX |
| |
| Wan Mingjian Xiao Xianci.A HIGH RESOLUTION SPATIAL SPECTRAL ESTIMATION METHOD BASED ON THE SVD OF A DATA MATRIX[J].Journal of University of Electronic Science and Technology of China(Social Sciences Edition),1989(2). |
| |
| Authors: | Wan Mingjian Xiao Xianci |
| |
| Institution: | Dept.of Electronic Engineering |
| |
| Abstract: | This paper presents a new method of spatial spectrum estimation based on the SVD (singular value decomposition) of a data matrix collected by the sensors of an array. The SNR can be improved by eliminating the smallest singular values which are the contributions of the noise.The spatial spectrum can be estimated by using the orthogonal properties of the 'noise' singular vecters and direction vecters of the array. In comparing with well known MUSIC spectral estimation algorithm, this method possesses better spectral resolution perfomance-and less computaional complexity, as well as better computational stability gained from the SVD itself. The method can be used in the high resolution direction finding system. |
| |
| Keywords: | spectral estimation algorithm singular value decomposition resolution array direction finding MUSIC algorithm Spatial |
| 本文献已被 CNKI 等数据库收录！ |
