Review of user parameter-free robust adaptive beamforming algorithms
Digital Signal Processing
Unitary ESPRIT: how to obtain increased estimation accuracy with areduced computational burden
IEEE Transactions on Signal Processing
Joint estimation of time delays and directions of arrival ofmultiple reflections of a known signal
IEEE Transactions on Signal Processing
ML estimator and hybrid beamformer for multipath and interference mitigation in GNSS receivers
IEEE Transactions on Signal Processing
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We address the 2D direction-of-arrival (DOA) estimation problem in scenarios with coherent sources. More specifically, we adopt beamforming solutions based on the iterative adaptive approach (IAA) recently proposed in the literature. The motivation of such adoption mainly comes from the excellent behavior these beamformers provide in scenarios with coherent sources. Nonetheless, these strategies suffer from a prohibitive computational complexity, especially in 2D scenarios. In order to alleviate the, we propose two reduced-complexity (RC) versions of the IAA and IAA based on maximum likelihood (IAA-ML) algorithms. The proposed beamformers are referred to as IAA-RC and IAA-ML-RC and provide similar results to those obtained with their original counterparts. Computational complexity, however, is further reduced. Numerical results presented in the paper show that the computational burden can be decreased by a 52% with our proposed solutions in the considered scenarios.