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New Methods for MLE of Toeplitz Structured Covariance Matrices with\n Applications to RADAR Problems

2021/10/23 by Augusto Aubry, Prabhu Babu, Aubry, Augusto +5
Computer Science · Engineering · #Direction-of-Arrival Estimation Techniques #FOS: Electrical engineering #Radar Systems and Signal Processing #Signal Processing (eess.SP) #Sparse and Compressive Sensing Techniques #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2110.12176

openalex publication_date 2021/10/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This work considers Maximum Likelihood Estimation (MLE) of a Toeplitz\nstructured covariance matrix. In this regard, an equivalent reformulation of\nthe MLE problem is introduced and two iterative algorithms are proposed for the\noptimization of the equivalent problem. Both the strategies are based on the\nMajorization Minimization (MM) framework and hence enjoy nice properties such\nas monotonicity and ensured convergence to a stationary point of the equivalent\nMLE problem. The proposed algorithms are also extended to deal with MLE of\nother related covariance structures, namely, the banded Toeplitz,\nToeplitz-block-Toeplitz, low rank Toeplitz structure plus a scalar matrix\n(accounting for white noise), and finally Toeplitz matrices satisfying a\ncondition number constraint. Through numerical simulations, it is shown that\nnew methods provide satisfactory performance levels in terms of both mean\nsquare estimation error and signal-to-interference-plus-noise ratio.\n

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