Abstract:

In order to solve the subband decomposition problem of the wideband signal with a large spectrum scope, a new method for nun-uniform subband decomposition based on Power Spectral Density (PSD) was proposed to dynamically adjust the number and bandwidth of subband, reasonably control the autocorrelation matrix eigenvalue spread of subband signals and improve the performance and efficiency of subband signal processing. For a given sequence, the number of subbands and the spectrum range of subband were determined through power spectrum estimation. Then the subband signal was shifted to zero frequency using subband modulation to achieve signal decomposition. The eigenvalue spread of subband signal and signal reconstruction performance were analyzed using Matlab. The experimental results show that, compared with the existing methods with equal number of subbands, the proposed one using the distribution information of PSD can effectively control the eigenvalue spread of subband while maintaining well signal reconstruction performance.

摘要：

针对频谱变化范围较大的宽带信号的子带分解问题，为了动态地调整子带的宽带与数量，合理地控制子带信号的自相关矩阵特征值扩散度，提高子带信号处理的性能和效率，在基于离散傅里叶变换(DFT)子带分解方法的基础上，提出了一种基于信号功率谱密度(PSD)的动态非均匀子带分解的新方法。对于给定序列，通过功率谱估计，确定子带数目和子带幅度范围，通过子带调制实现不同子带向零频处搬移，实现信号的分解。利用Matlab对子带信号特征值扩散度和信号重建性能进行了仿真。实验结果表明，与均匀子带分解相比，提出的方法直接利用PSD的分布信息实现非均匀子带分解，有效地控制了子带信号特征值扩散度在合理范围内的分布，并具有较好的重构性能。