基于空间时频分布的欠定混合信号源个数估计

针对欠定混合信号的源个数估计问题,提出了一种基于空间时频分布与奇异值分解的估计算法,把所有自源时频点对应的空间时频分布矩阵组成三阶张量,把欠定混合问题转化为超定问题,通过对三阶张量对应的矩阵进行奇异值分解估计出源信号的数目,该方法不需要假设源信号是稀疏的或独立的,理论分析和仿真结果验证了算法的有效性.

Estimation of the Sources Number in the Underdetermined Mixture Signals Based on Spatial Time-frequency Distribution

Aiming at the problem of estimation of the sources number in the underdetermined mixture signals, this paper propose a algorithm based on spatial time-frequency distribution (STFD) and singular value decomposition (SVD) without the assumption of sparsity and independence. First, the time-frequency distribution matrices corresponded to the auto-source TF points was stacked in three-order tensor, then the entries of the tensor stacked in matrix and SVD on this matrix was performed to finish the estimation of the sources number. The efficiency of the algorithm was proved in theory. Computer simulations show that the proposed recognition algorithm is high in performance.