TY  - RPRT
TI  - Hilbert-Based Clustering Approach for Linear Arrays
AV  - public
ID  - elediasc12888
Y1  - 2024/06/07/
UR  - http://www.eledia.org/students-reports/888/
KW  - Local Optimization
KW  -  Array Synthesis
KW  -  Sub-Arraying
N2  - 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.
A1  - BENONI, Arianna
A1  - ROCCA, Paolo
A1  - ANSELMI, Nicola
A1  - MASSA, Andrea
M1  - technical_report
PB  - ELEDIA Research Center - University of Trento
ER  -