Sparsening Conformal Arrays Through a Versatile BCS-Based Method - Oliveri, Giacomo; Bekele, Ephrem T.; Robol, Fabrizio; Massa, Andrea (IEEE transactions on antennas and propagation, 2014)
Sparsening conformal arrangements is carried out through a versatile Multi-Task Bayesian Compressive Sensing (MT-BCS) strategy. The problem, formulated in a probabilistic fashion as a pattern-matching synthesis, is that of determining the sparsest excitation set (locations and weights) fitting a reference pattern subject to user-defined geometrical constraints. Results from a set of representative numerical experiments are presented to illustrate the key-features of the proposed approach as well as to assess, also through comparisons, its potentials in terms of matching accuracy, element saving, and computational costs.