Stochastic Analysis of the Impact of Substrate Compression on the Performance of Textile Antennas.

One of the many adverse effects modifying the performance of textile antennas in real operating conditions is substrate compression. Therefore, this communication presents a stochastic collocation method (SCM) that either relies on the generalized polynomial chaos (gPC) expansion or on a novel Hermite-Padé approximant. The method is introduced to rigorously quantify the effect of random variations in the height and the permittivity of the substrate on the figures of merit of a textile antenna. Next, the joint height and permittivity probability distribution of a compressible substrate are characterized by means of a new measurement setup based on a resonant-perturbation technique. Finally, the method is validated for a probe-fed GPS textile antenna. It is shown that Hermite-Padé approximants model the highly nonlinear relationship between these substrate random variables and the figures of merit of the antenna more efficiently than the gPC. Moreover, a Kolmogorov–Smirnoff test proves that the resulting distributions of the antenna’s figures of merit are as accurate as those obtained by means of a Monte-Carlo (MC) analysis, with demonstrated speedup factors up to 123. [ABSTRACT FROM PUBLISHER]