一种新的基于Krylov子空间的快速子空间分解  

New fast subspace decomposition based on Krylov subspace

作　　者：安志娟[1,2] 苏洪涛[2] 包志强[2] 保铮[2] 

机构地区：[1]西安电子科技大学理学院,陕西西安710071 [2]西安电子科技大学雷达信号处理重点实验室,陕西西安710071

出　　处：《系统工程与电子技术》2009年第1期29-32,共4页Systems Engineering and Electronics

基　　金：国防预研基金资助课题(9140A07040308DZ0119)

摘　　要：快速有效地进行子空间分解是子空间类算法走向工程应用的关键。提出了一种新的期望信号的选择方法,并证明了在空时白噪声条件下由观测信号的协方差矩阵及观测信号与期望信号的互相关矢量构成的Krylov子空间等价于信号子空间,从而可以通过多级维纳滤波方法计算Krylov子空间的基来实现信号子空间的快速估计。由仿真实验可以看出所提出的方法能够快速有效地实现子空间分解,尤其在低信噪比下仍然具有较高的性能。Fast and effective decomposition of subspace is important to the engineering application of subspace-based algorithms. A new form of the desired signal is presented, and that in the context of space-time white noise the Krylov subspaee of both the covariance matrix of the Observation signal and the crosscorrelation vector between the observation signal and the desired signal is equivalent to the signal subspace is proved, thus the fast estimation of signal subspace can be realized by computing the basis of the Krylov subspace with the multi-stage Wiener filter （MSWF）. By simulation, it is clear that the proposed method can perform the fast subspace decomposition effectively, especially in the case of lower signal to noise ratio.

关 键 词：阵列 参数估计 子空间分解 期望信号 KRYLOV子空间 多级维纳滤波 

分 类 号：TN911.7[电子电信—通信与信息系统]