Multiple-measurement vector based implementation for single-measurement vector sparse Bayesian learning with reduced complexity
Complexity reduced MMV based implementation for SMV sparse Bayesian learning (SBL) is proposed. Optimal solution for the MMV formulation is shown to be the same with the SMV formulation. Two suboptimal solutions based on multitask Bayesian compressive sensing and simultaneous SBL are proposed. Maximal ratio combining is applied to exploit deterministic correlation to improve estimation performance.
sparse bayesian learning compressive sensing direction of arrival estimation