Feb 9, 2023 · Recently, the sparse Bayesian learning (SBL) technique is increasingly exploited, which outperforms conventional compressive sensing (CS) ...
An off-grid space alternating multisnapshot SBL (OGSA-MSBL) approach used for DOA and source amplitude estimation is proposed in this article, which introduces ...
In this paper, different from the present DOA estimation methods, both the off-grid gap due to the sparse sampling and the unknown mutual coupling effect ...
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What is sparse Bayesian learning?
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Most common approach is to reduce the parameter space to a fixed grid of points, thus restricting the solution space. [12] proposes off-grid sparse ...
2 days ago · Therefore, we propose an improved DOA estimation algorithm based on off-grid root SBL and pseudo-noise resampling for massive MIMO systems.
In this study, we present a deep sparse Bayesian learning (DSBL) network to solve this problem. We first establish the signal model for off-grid DOA with NA.
Direction of arrival (DOA) and source amplitude estimation are widely encountered in detection and communication as traditional array processing problems.
The existing off-grid sparse Bayesian learning (SBL) DOA estimation method for nested arrays suffers from two major drawbacks: reduced array aperture and ...
For direction-of-arrival (DOA) estimation problems, sparse Bayesian learning (SBL) has achieved excellent estimation performance, especially in sparse arrays.
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Thus, researchers typically employ grid refinement, continuous−domain parameter estimation, or Bayesian learning−based methods to enhance reconstruction ...