...效分布源图等;另一类是偶极源定位方法,具体有非线性最小二乘法、全局优化算法、子空间分解算法(multiple signal classification,MUSIC)[1],以及假设源呈三维体分布的低分辨层析方法[2]。
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通过对相关矩阵进行特征值分解，估计信号子空间和噪声子空间，并利用MU S IC算法估计宽带LF M信号的波达方向。
Through estimating the signal and noise subspaces with the eigen-decomposition of the correlation matrix, the MUSIC algorithm is used to estimate the DOAs of LFM sources.
基于子空间分解的ESPRIT算法常用在阵列处理中对目标进行DOA估计。
ESPRIT algorithm based on subspace decomposition is usually used to estimate the direction of arrival (DOA) of source in array signal processing.
但盲估计算法，如子空间分解法等，需要较大的样本值，收敛速率慢，不利于实时信道估计。
But the blind estimation algorithm, for example, the sub-space decomposition, is not good for real time estimation because it requires large received signals, and has low estimation convergence rate.
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