Polynomial chaos

Mathematics

Basis function

Gene

Algorithm

Statistics

Mathematical optimization

Machine learning

Variogram

Mathematical analysis

Directivity

Antenna (radio)

Chemistry

Monte Carlo method

Programming language

Computer science

Kriging

Biochemistry

Robustness (evolution)

Telecommunications

Metamodeling

Polynomial

International Journal of Numerical Modelling Electronic Networks Devices and Fields

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.

Efficient yield estimation of multiband patch antennas by polynomial chaos‐based Kriging