Paper Info
Title
Quasi-Global Optimization of Antenna Structures Using Principal Components and Affine Subspace-Spanned Surrogates.
Abstract
Parametric optimization is a mandatory step in the design of contemporary antenna structures. Conceptual development can only provide rough initial designs that have to be further tuned, often extensively. Given the topological complexity of modern antennas, the design closure necessarily involves full-wave electromagnetic (EM) simulations and & x2014;in many cases & x2014;global search procedures. Both factors make antenna optimization a computationally expensive endeavor: population-based metaheuristics, routinely used in this context, entail significant computational overhead. This letter proposes a novel approach that interleaves trust-region gradient search with iterative parameter space exploration by means of local kriging surrogate models. Dictated by efficiency, the latter are rendered in low-dimensional subspaces spanned by the principal components of the antenna response Jacobian matrix, extracted to identify the directions of the maximum (frequency-averaged) response variability. The aforementioned combination of techniques enables quasi-global search at the cost comparable to local optimization. These features are demonstrated using two antenna examples as well as benchmarking against multiple-start local tuning.
Year
DOI
Venue
2020
10.1109/ACCESS.2020.2980057
IEEE ACCESS
Keywords
DocType
Volume
Antenna optimization,EM-driven design,gradient-based search,principal component analysis,kriging
Journal
8
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Jon Atli Tomasson100.34
S Koziel2521101.41
Anna Pietrenko-Dabrowska324.92