most citedDeep Learning-Aided Subspace-Based DOA Recovery for Sparse Arrays

1 citations · 1 across the 1 of their papers we have counts for

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eess.SP2023★ 1 cited

Deep Learning-Aided Subspace-Based DOA Recovery for Sparse Arrays

Yoav Amiel, Dor H. Shmuel, Nir Shlezinger +1

Sparse arrays enable resolving more direction of arrivals (DoAs) than antenna elements using non-uniform arrays. This is typically achieved by reconstructing the covariance of a vi…

eess.SP2023

SubspaceNet: Deep Learning-Aided Subspace Methods for DoA Estimation

Dor H. Shmuel, Julian P. Merkofer, Guy Revach +2

Direction of arrival (DoA) estimation is a fundamental task in array processing. A popular family of DoA estimation algorithms are subspace methods, which operate by dividing the m…