Rapid Multi-Band Patch Antenna Yield Estimation using Polynomial Chaos-Kriging
Abstract
Yield estimation of antenna systems is important to check their robustness with respect to the uncertain sources. Since the Monte Carlo sampling-based real physics simulation model evaluations are computationally intensive, this work proposes the polynomial chaos-Kriging (PC-Kriging) metamodeling technique for fast yield estimation. 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 is demonstrated with an analytical case and a multi-band patch antenna case and compared with direct PCE and Kriging metamodels. In the analytical case, PC-Kriging reduces the computational cost by around 42% compared with PCE and over 94% compared with Kriging. In the antenna case, PC-Kriging reduces the computational cost by over 60% compared with Kriging and over 90% compared with PCE. In both cases, the savings are obtained without compromising the accuracy.
Recommended Citation
X. Du et al., "Rapid Multi-Band Patch Antenna Yield Estimation using Polynomial Chaos-Kriging," Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11538 LNCS, pp. 487 - 494, Springer, Jan 2019.
The definitive version is available at https://doi.org/10.1007/978-3-030-22744-9_38
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Kriging; Microstrip multi-band patch antenna; Monte Carlo sampling; PC-Kriging; PCE; Yield estimation
International Standard Book Number (ISBN)
978-303022743-2
International Standard Serial Number (ISSN)
1611-3349; 0302-9743
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023, All rights reserved.
Publication Date
01 Jan 2019
