Effective approach for pattern synthesis of sparse reconfigurable antenna arrays with exact pattern matching

Abstract

An effective approach is presented for pattern synthesis of reconfigurable antenna arrays with non-uniformly spaced arrangements. On the basis of the joint sparse model of multiple reference patterns, the proposed approach can dynamically reconfigure multiple radiation patterns with exactly matched pattern details and minimum number of antenna elements by joint optimisation of element positions and excitations. In this study, the design of sparse reconfigurable arrays is recast as a simultaneous sparse approximation problem and solved with the multi-task Bayesian compressive sensing. The common element positions and individual element excitations for multiple radiation patterns are obtained simultaneously by searching out multiple weight vectors sharing the same prior probability. Several representative experiments are provided to validate the effectiveness of the proposed method for the design of maximally sparse reconfigurable antenna arrays with exact pattern matching.