Enhanced Linear Array Clustering via Hilbert Order

BENONI, Arianna and ROCCA, Paolo and ANSELMI, Nicola and MASSA, Andrea (2024) Enhanced Linear Array Clustering via Hilbert Order. Technical Report. ELEDIA Research Center - University of Trento.

[img] Text
Enhanced_Linear_Array_Clustering_via_Hilbert_Order.pdf

Download (1MB)

Abstract

This study investigates the clustering of linear phased arrays (PAs) featuring complex weights. By exploiting the inherent locality-preserving characteristic of the Hilbert curve, an initial reduction of problem dimensionality is performed. Subsequently, a basic clustering algorithm is employed to enhance the alignment of the radiated pattern with a predetermined reference. We systematically explore both contiguous and noncontiguous partitions of the Hilbert-ordered list of complex excitations to comprehensively sample the solution space. Representative results, including reference PAs generating steered pencil and shaped beams, are included to highlight the superior performance of the presented approach over conventional k-means algorithms.

Item Type: Monograph (Technical Report)
Uncontrolled Keywords: Local Optimization, Array Synthesis, Sub-Arraying
Subjects: A Areas > A WC Next Generation Wireless Communications
M Methodologies > M AT Analytic Techniques
URI: http://www.eledia.org/students-reports/id/eprint/887

Actions (login required)

View Item View Item