Bayesian Inference in Action in EMC—Fundamentals and Applications

The scope of this study is to introduce the reader to Bayesian inference applied to the evaluation of measurement uncertainty and conformity assessment in the field of radiofrequency (RF) and electromagnetic compatibility (EMC) measurements and testing. The advantages stemming from the use of Bayesian inference with respect to the consolidated theoretical framework provided by the Guide to the Expression of Uncertainty in Measurement (widely known as the “GUM”) are emphasized, also in order to appreciate the reasons behind the ongoing revision of the same GUM. An important result of Bayesian inference has been already implemented in two guides to the evaluation of EMC measurement uncertainty, namely, the IEC TR 61000-1-6 and the standard ANSI C63.23. Further, it is here shown that through Bayesian inference mathematical tools can be derived for the assessment of conformity of distribution of values, such as the electric field over a surface, taking into proper account both the intrinsic variability among the values of the distribution and the measurement uncertainty of each value. The theoretical background is first introduced and then two applications of Bayesian inference to measurement uncertainty and conformity assessment in the field of RF and EMC measurements and testing are thoroughly described.