宽带信号子空间谱估计修正方法的研究

Research on the Improved Methods of Wideband Signal-Subspace Spatial-Spectrum Estimation

提出了信号子空间维数估计法、噪声子空间加权法和扩展MUSIC法三种修正的宽带信号子空间谱估计方法,它们均有效地解决了宽带信号子空间谱估计法所存在的信号子空间维数扩展问题。信号子空间维数估计法用包含信号99.9%以上功率的特征值数目来估计信号子空间维数,正确地划分了子空间。噪声子空间加权法和扩展MUSIC法不用划分子空间,而是给噪声子空间特征向量或全空间特征向量加权,减小了子空间维数扩展的影响。仿真实验结果表明:三种修正方法是有效的,并具有良好的统计性能。

To overcome the problem of signal-subspace dimension expanding, three different improved methods for wideband signal-subspace spatial-spectrum estimation are presented. The first method, called the signal-subspace dimension estimation method, estimates signal-subspace dimension by a number of eigenvalues, which include 99.9% signal power; thus this method can make a correct division between signal-subspace and noise-subspace. The other two methods, weighted noise-subspace method and extended MUSIC method, do not need to make a correct division between the two subspaces. Instead. These two methods can reduce the effect of signal-subspace dimension expanding directly by using weighted eigenvectors in the noise-subspace or the entire space. Computer simulations show that all these improved methods can overcome effectively the effect of signalsubspace dimension expanding of wideband signal-subspace spatial-spectrum estimation and possess good statistical performance.