Numerical Techniques for the Maximum Likelihood Toeplitz Covariance Matrix Estimation: Part I. Symmetric Toeplitz Matrices
Signal Processing
2025-07-03 v1 Information Theory
math.IT
Abstract
In several applications, one must estimate a real-valued (symmetric) Toeplitz covariance matrix, typically shifted by the conjugated diagonal matrices of phase progression and phase "calibration" errors. Unlike the Hermitian Toeplitz covariance matrices, these symmetric matrices have a unique potential capability of being estimated regardless of these beam-steering phase progression and/or phase "calibration" errors. This unique capability is the primary motivation of this paper.
Cite
@article{arxiv.2507.01230,
title = {Numerical Techniques for the Maximum Likelihood Toeplitz Covariance Matrix Estimation: Part I. Symmetric Toeplitz Matrices},
author = {Yuri Abramovich and Victor Abramovich and Tanit Pongsiri},
journal= {arXiv preprint arXiv:2507.01230},
year = {2025}
}