📝 SummarXiv

Abstract

We introduce an efficient implementation of sparse recovery methods for the problem of harmonic estimation with 2D sparse arrays using a single snapshot. By imposing a uniformity constraint on the harmonic grids of the subdictionaries used in the sparse recovery problem, in addition to a mild constraint on the array topology that consists in having the elements lie on a grid specified in half-wavelength units, we show that the Gram matrices that appear in these sparse recovery methods exhibit a block-circulant with circulant blocks (BCCB) structure. The BCCB structure is then exploited to reduce the computational complexity of the matrix-vector products that appear in these methods through the use of 2D fast Fourier transforms (FFT) from O((L1L2)^2) down to O(L1L2 log(L1L2)) operations per iterations, where L1, L2 are the lengths of the subdictionaries used for estimating the harmonics in the first and second dimension, respectively. We experimentally verify the proposed implementation using the iterative shrinkage thresholding algorithm (ISTA), the fast iterative shrinkage-thresholding algorithm (FISTA), and the alternating direction method of multipliers (ADMM) where we observe improvements