%D 2024
%X This study investigates the clustering of linear phased arrays (PAs)
employing complex weights. Leveraging the inherent locality-preserving
nature of the Hilbert curve, an initial reduction of problem dimensionality
is performed. Subsequently, a basic clustering algorithm is adopted to
enhance the alignment of the radiated pattern with a predefined reference.
Both contiguous and noncontiguous partitions of the Hilbert-ordered list of
complex excitations are comprehensively evaluated to systematically explore the
solution space. Representative results, including reference PAs generating
steered pencil and shaped beams, are presented for validation and to highlight
the superior performance of the proposed approach over conventional k-means algorithms.
%I ELEDIA Research Center - University of Trento
%A Arianna BENONI
%A Paolo ROCCA
%A Nicola ANSELMI
%A Andrea MASSA
%K Local Optimization, Array Synthesis, Sub-Arraying
%T Clustering Complex Excitations in Linear Arrays with Hilbert Ordering
%L elediasc12889