Gridless methods for underdetermined source estimation

Abstract

The performances of two gridless algorithms for direction of arrival estimation are analyzed, when the number of sources can be larger than the number of array elements. One of these algorithms is a hybrid scheme recently proposed by the authors that uses low rank recovery techniques, and the other is based on total variation (TV) norm minimization scheme. It is shown that when a nested sensor array is used, and the source signals are assumed to be Gaussian, these recovery algorithms can recover O(M^2) sources using M sensors with overwhelming probability in the number of time snapshots.

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