On the computation of the multivariate structured total least squares estimator

A multivariate structured total least squares problem is considered, in which the extended data matrix is partitioned into blocks and each of the blocks is Toeplitz/Hankel structured, unstructured, or noise free. Two types of numerical solution methods for this problem are proposed: (i) standard local optimization methods in combination with efficient evaluation of the cost function and its first derivative, and (ii) an iterative procedure proposed originally for the element-wise weighted total least squares problem. The computational efficiency of the proposed methods is compared with this of alternative methods. Copyright (C) 2004 John Wiley Sons, Ltd.