Direction-of-arrival (DOA) estimation based on sparse Bayesian learning (SBL) framework has attracted extensive attention. The accuracy of on-grid DOA estimation is restricted by the prescribed grid, while off-grid ap...
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Direction-of-arrival (DOA) estimation based on sparse Bayesian learning (SBL) framework has attracted extensive attention. The accuracy of on-grid DOA estimation is restricted by the prescribed grid, while off-grid approaches resolves the problem of grid mismatch partly. This letter deals with off-grid DOA estimation problem of wideband signals. A factor graph is designed to describe the problem with Dirichlet process (DP) prior, which clusters the sparse structure of wideband signals. The authors employ the combined belief propagation-mean field (bp-mf) rule on the factor graph and lead to a message passing algorithm. Simulation results verify the superiority of the proposed combined bp-mf algorithm for off-grid DOA estimation compared to other state-of-art methods.
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