Location:
Search - subspace evd
Search list
Description: 用子空间分解法求出时延估计，这种方法具有较强的抗噪声性能-Calculated using subspace decomposition delay estimation, this method has strong anti-noise performance
Platform: |
Size: 1024 |
Author: 闫晓媛 |
Hits:
Description: 针对非圆信号DOA估计问题,提出了一种基于实值特征值分解 (Eigenvalue decomposition,EVD)的求根MUSIC算法.首先利用非圆信号为实值信号的特点,将阵列上的接收数据及其共轭用欧拉公式转换为实值正弦与 余弦数据,然后将正弦与余弦数据进行串联,从而扩展了数据维数.由于采用实值矩阵的EVD,因此在EVD阶段的运算量简化为复值EVD的1/4.根据 EVD后获得的信号与噪声子空间的特点,对噪声子空间和导向矩阵进行重构以便于可以使用求根MUSIC算法获取对DOA的估计.仿真实验验证了本文算法的 有效性-For the estimation of noncircular signals of DOA, proposes a decomposition value based on real valued features (Eigenvalue decomposition, EVD) the root MUSIC algorithm. Firstly, characteristics of non circular signals for real valued signals, the array data and its conjugate with the Euler formula into real value of sine and cosine and sine and cosine data. The data series, thus expanding the dimension of the data. Because of the use of real valued matrix computation in EVD, so the EVD stage was simplified as a complex valued EVD 1/4. according to the characteristics of signal and noise subspace is obtained after EVD, the noise subspace and orientation matrix reconstruction in order to facilitate the use of DOA can obtain the estimated root MUSIC the algorithm. The simulation results verify the effectiveness of the proposed algorithm
Platform: |
Size: 2048 |
Author: maomaoyu |
Hits: