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本文提出了一种新的自适应频谱估计技术,该技术把共轭梯度法应用于自适应频谱分析问题,即用共轭梯度法迭代地求出半定埃尔米持矩阵的相应于最小广义特征值之广义特征矢量。通过计算机仿真把这种新的方法与现有的方法进行了比较。从本文所提供的有限的例子中可看出新方法在计算上更高效,但占用更多的存储空间。此外,本方法可有效地对短的数据记录进行频谱分析;而且如能得到噪声的协方差矩阵估计,则还能进行噪声修正,从而得到无偏的频谱估计。本技术对窄带和宽带信号的分析效果都很好。
In this paper, a new adaptive spectrum estimation technique is proposed, which applies the conjugate gradient method to the problem of adaptive spectrum analysis. That is, the conjugate gradient method is used to iteratively determine the minimum generalized characteristic The generalized eigenvector of value. This new method is compared with existing methods by computer simulation. From the limited examples provided in this paper, we can see that the new method is computationally more efficient but takes up more storage space. In addition, this method can effectively spectrum analyze short data records, and if noise covariance matrix estimation can be obtained, noise correction can be performed to obtain unbiased spectrum estimation. The technology of narrowband and wideband signal analysis are good.