Power pattern matching through the hybrid Bayesian compressive sensing

In this work, the synthesis problem of sparse linear arrays complying with user defined power masks is addressed by means of a Compressive Sensing (CS)-based methodology. A novel hybrid Bayesian CS (BCS) approach integrating a mask-constrained synthesis within a BCS solver is proposed, enabling an effective and efficient tool for the design of sparse arrays, starting from arbitrary user-defined requirements. A simple example validating the proposed approach is reported and discussed.