TY  - RPRT
M1  - technical_report
N2  - 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.
TI  - Enhanced Linear Array Clustering via Hilbert Order
UR  - http://www.eledia.org/students-reports/887/
Y1  - 2024/05/31/
AV  - public
PB  - ELEDIA Research Center - University of Trento
KW  - Local Optimization
KW  -  Array Synthesis
KW  -  Sub-Arraying
ID  - elediasc12887
A1  - BENONI, Arianna
A1  - ROCCA, Paolo
A1  - ANSELMI, Nicola
A1  - MASSA, Andrea
ER  -