Compressive Beamforming Based on Multiconstraint Bayesian Framework

Compressive sensing (CS) is a promising technique recognized for its merits in recovering sparse signals with enhanced resolution entailing specific constraints. In recasting the CS model within a Bayesian framework, its formulation can be interpreted and solved under various prior assumptions that may correspond to, e.g., the $\mathcal {L}_{1}$ 更多