Yield estimation of antenna systems is important to check their robustness with respect to the uncertain sources. Since direct Monte Carlo sampling of accurate physics-based models can be computationally intensive, this work proposes the use of the polynomial chaos–Kriging (PC-Kriging) metamodeling method for fast yield estimation of multiband patch antennas. PC-Kriging integrates the polynomial chaos expansion (PCE) as the trend function of Kriging metamodel since the PCE is good at capturing the function tendency and Kriging is good at matching the observations at training points. The PC-Kriging method is demonstrated on two analytical cases and two multiband patch antenna cases and is compared with the PCE and Kriging metamodeling methods. In the analytical cases, PC-Kriging reduces the computational cost by over 40% compared with PCE and over 94% compared with Kriging. In the antenna cases, PC-Kriging reduces the computational cost by over 60% compared with Kriging and over 90% compared with PCE. In all cases, the savings are obtained without compromising the accuracy.


Mechanical and Aerospace Engineering


Icelandic Centre for Research, Grant 174573‐052

Keywords and Phrases

antenna yield estimation; Kriging; microstrip multiband patch antenna; Monte Carlo sampling; polynomial chaos expansions; polynomial chaos-based Kriging

International Standard Serial Number (ISSN)

1099-1204; 0894-3370

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





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Publication Date

01 Nov 2020