A Stochastic Study of Large Arrays Related to the Number of Electrically Large Aperture Radiators

A study of the maximally sparse large planar arrays with electrically large elements is presented. The conditional probabilities of the element placements and their resulting auxiliary radiation integrals are derived. Through them the average and the directivity pattern formulas are also derived. Employing these formulas, we present a convex method that provides a solution to the maximally sparse problem when main lobe constraints are imposed on the directivity pattern. In particular, by taking the possible types of elements into account, we manage to obtain the lower bound of the directivity that an array should exhibit. This lower bound is analytically derived in the form of a Pareto (sub-) set that classifies the possible arrays into feasible and nonfeasible ones. This Pareto set can also enable tradeoff studies to be conducted without the need to consider the full range of every parameter. From the procedure, several acceptable combinations of elements are obtained. Simulation results, which confirm the methodology, are presented.