中文摘要：

针对存在加性高斯白噪声多参数变量的单自旋回波串信号参数估计问题,提出一种参数分离化的2-D参数估计方法.利用2-D数据矩阵秩为1的特性,依照迭代加权最小二乘方法,从左、右主奇异值向量中以参数分离的方式分别估计出衰减因子和频率,基于最小二乘方法进一步获得信号幅度估计.该方法在相对高信噪比和/或大数据样本下可达到克拉美罗下界,且计算复杂度较低.仿真数据结果证明了算法的有效性.

英文摘要：

In allusion to multi-parameter estimation of a spin echo train（SET） signal in the presence of additive white Gaussian noise,a two-dimensional（2-D） parameter estimation method in a separable manner is proposed.By utilizing the rankone property of the 2-D data matrix,the damping factor and frequency are estimated in a separable manner from the principal left and right singular vectors according to an iterative weighted least squares（WLS） method.The complex amplitude of SET is then obtained on the basis of standard least squares.The parameter estimation performance of this method achieves Cramer-Rao lower bound（CRLB） at relatively large signal-to-noise ratio（SNR） and/or data size conditions.Simulation results show the effectiveness of the proposed algorithm.