Efficient stochastic transmission line modeling using polynomial chaos expansion with multiple variables

The polynomial chaos expansion (PCE) is widely used in computational electromagnetics to model stochastic parameters and uncertainty. The major drawback of PCE is that the computational costs grow exponentially with the number of stochastic variables. This work presents a systematic and numerically efficient approach for the application of PCE to cascaded transmission lines where the characteristic impedances are stochastically given and independent from each other. As an example, a stepped impedance filter is analyzed containing up to 31 transmission line segments. The modeling approach is validated with Monte-Carlo (MC) and shows a very good agreement and a significant speedup. The presented method is valid for concatenation of any passive linear circuit.