I. Title:Advanced Methods for MLE of Toeplitz Structured Covariance Matrices with Applications to RADAR Problems

II. Presenter:The University of Naples Federico II, Augusto Aubry, Associate Professor

III. Time:14:30-15:30, July 15, 2026

IV. Location:KC218, Qingshuihe Campus

V. Host:YU Xianxiang,Research Fellow

VI. Overview:

In this talk, the maximum likelihood estimation (MLE) of covariance matrices with Toeplitz structure will be addressed. First, an equivalent reformulation of the MLE problem that is more amenable to optimization is derived. Building on this formulation, two iterative algorithms based on the majorization–minimization (MM) framework are developed.

The proposed methods guarantee monotonic improvement of the objective function and convergence to a stationary point. The framework is further extended to handle other practically relevant covariance structures, including banded Toeplitz, block Toeplitz, and Toeplitz-block-Toeplitz matrices.

Numerical results demonstrate that the proposed algorithms achieve estimation accuracy close to the Cramér–Rao bound (CRB) and provide strong performance in terms of signal-to-interference-plus-noise ratio (SINR). Moreover, they significantly reduce computational complexity compared with conventional approaches based on semidefinite programming (SDP), showing their potential value in practical radar signal processing problems.

VII.About the Presenter:

Augusto Aubry received the Dr. Eng. degree in telecommunication engineering with honors and the Ph.D. degree in electronic and telecommunication engineering from the University of Naples Federico II, Naples, Italy, in 2007 and 2011, respectively. From February to April 2012, he was a Visiting Researcher with Hong Kong Baptist University, Hong Kong. He is currently an Associate Professor with the University of Naples Federico II.

His research interests include statistical signal processing and optimization theory, with emphasis on MIMO communications and radar signal processing. Dr. Aubry is a Senior Member of IEEE. He received the 2022 IEEE Fred Nathanson Memorial Award as the young AESS Radar Engineer 2022, with the citation “For outstanding contributions to the application of modern optimization theory to radar waveform design and adaptive signal processing.” He was also a co-recipient of the 2013 IEEE Transactions on Aerospace and Electronic Systems Best Paper Award, entitled to the M. Barry Carlton Award, for the paper “Knowledge-Aided (Potentially Cognitive) Transmit Signal and Receive Filter Design in Signal-Dependent Clutter.”