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math.ST2015
Cramer-Rao Bound for Sparse Signals Fitting the Low-Rank Model with Small Number of Parameters
Mahdi Shaghaghi, Sergiy A. Vorobyov
In this paper, we consider signals with a low-rank covariance matrix which reside in a low-dimensional subspace and can be written in terms of a finite (small) number of parameters…
math.ST2015★ 97 cited
Subspace Leakage Analysis and Improved DOA Estimation with Small Sample Size
Mahdi Shaghaghi, Sergiy A. Vorobyov
Classical methods of DOA estimation such as the MUSIC algorithm are based on estimating the signal and noise subspaces from the sample covariance matrix. For a small number of samp…
math.ST2012★ 2 cited
Spectral Estimation from Undersampled Data: Correlogram and Model-Based Least Squares
Mahdi Shaghaghi, Sergiy A. Vorobyov
This paper studies two spectrum estimation methods for the case that the samples are obtained at a rate lower than the Nyquist rate. The first method is the correlogram method for…