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中文摘要：
利用平移不变结构阵列信号子空间的旋转不变性，构造一组具有对角结构的空时相关矩阵组。给出一种高精度的信号子空间估计方法，利用估计的信号子空间做降维矩阵处理空时相关矩阵组，从而减少计算量并加快收敛速度。基于非线性最小二乘建立代价函数，提出一种三迭代算法求解代价函数进而估计波达方向DOA。仿真结果证实该算法收敛速度较快，估计精度显著高于TLS-ESPRIT算法，尤其在低信噪比和小快拍数据下估计精度显著增强。
英文摘要：
The underlying rotational invariance among signal subspace induced by an array of sensors with a displacement invariance structure is exploited, and a set of spatio-temporal correlation matrices possessing diagonal structure are introduced. Consequently, a method is developed which gives a robust and precise estimation of signal subspace from the spatio-temporal correlation matrices. To make the computational complexity lower and the convergence speed faster, the high quality signal subspace is used as a dimension-reduction matrix dealing with the set of correlation matrices. A novel cost function is proposed based on nonlinear least squares. Afterwards, a new approach termed tri-iterative algorithm（TIA） is derived for solving the cost function and estimating the direction of arrival of sources. Simulation results shows that the proposed TIA algorithm has good performance in convergence, and the estimation accuracy is improved considerably. It is a new reliable algorithm which is particularly accurate in extremely low SNR and small snapshots.
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Convolutive blind source separation based on joint block Toeplitzation and block-inner diagonalizati
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