Measurement Uncertainty Estimation for Electromagnetism Devices and Equipment Using Extreme Fisher Information

In electromagnetism devices and equipment measurement activities, it is hard to identify and compensate every effect in measurement and evaluate the incompleteness of the measurement results accurately and efficiently. In this paper, we employ the probability density functions (PDFs) derived from the extreme Fisher information (EFI) method in the view of information theory for estimating the measurement uncertainty of the measurement result. By considering the physical essence of EFI, a differential equation model is established for the measurement practice and the explicit form of the solution PDF corresponding to EFI is given, which guarantees the dynamics and the practicability of the estimation of the measurement uncertainty (MU). The obtained the PDF can describe the combined performance of the system and all the measurement effects, then, with the PDF and the confidence, MU can be estimated more dynamically and efficiently. The effectiveness of the proposed EFI method is demonstrated by the numerical results of two practical instances.