Hilbert-Based Clustering Approach for Linear Arrays

BENONI, Arianna and ROCCA, Paolo and ANSELMI, Nicola and MASSA, Andrea (2024) Hilbert-Based Clustering Approach for Linear Arrays. Technical Report. ELEDIA Research Center - University of Trento.

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Abstract

This research examines the clustering of linear phased arrays (PAs) incorporating complex weights. Through exploitation of the intrinsic locality-preservation property associated with the Hilbert curve, the problem's dimensionality is decreased. Subsequently, a basic clustering algorithm is employed to optimize the alignment of the radiated pattern with a predetermined reference. We systematically assess both contiguous and noncontiguous partitions of the Hilbert-ordered list of complex excitations to comprehensively sample the solution space. Representative outcomes, encompassing reference PAs generating steered pencil and shaped beams, are provided for validation and to underscore the efficacy of our methodology relative to state-of-the-art k-means algorithms.

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