Beampattern Synthesis using Reweighted l1-Norm Minimization and Array Orientation Diversity

Abstract

The pattern synthesis of sparse antenna arrays has many practical applications in situations where the weights, size, and cost of antennas are limited. In this work the antenna array synthesis problem, with minimum number of elements, is studied from the new perspective of sparseness constrained optimization. The number of antenna elements in the array can be efficiently reduced by casting the pattern synthesis problem into the compressive sensing (CS) framework of sparseness constrained optimization and solving with the reweighted l1-norm minimization algorithm. Besides, the proposed method allows exploitation of the array orientation diversity in the CS framework to address left-right radiation pattern ambiguity problem. Numerical examples are presented to show the high efficiency of achieving the desired radiation pattern with the minimum number of antenna elements.

Keywords

• Sparse array pattern synthesis
• reweighted l1-norm minimization
• orientation diversity
• convex optimization