Statistical-Physical Models of Electromagnetic Interference

TLDR

Electromagnetic interference is a highly non‑Gaussian noise source that can severely degrade system performance and is a key concern for spectral management. The study aims to develop analytically tractable, experimentally verifiable statistical‑physical models of electromagnetic interference. The authors classify interference into Class A (narrowband), Class B (broadband), and Class C (combined), and construct first‑order statistical models yielding analytic expressions for exceedance probabilities and probability densities. The resulting models are canonical, with Class A described by a 3‑parameter model and Class B by a 6‑parameter model, independent of specific source parameters.

Abstract

Most man-made and natural electromagnetic interference, or "noise," are highly non-Gaussian random processes, whose degrading effects on system performance can be severe, particularly on most conventional systems, which are designed for optimal or near optimal performance against normal noise. In addition, the nature, origins, measurement, and prediction of the general EM interference environment are a major concern of any adequate spectral management program. Accordingly, this study is devoted to the development of analytically tractable, experimentally verifiable, statistical-physical models of such electromagnetic interference. Here, classification into three major types of noise is made: Class A (narrow band vis-á-vis the receiver), Class B (broad band vis-á-vis the receiver), and Class C (= Class A + Class B). First-order statistical models are constructed for the Class A and Class B cases. In particular, the APD (a posteriori probability distribution) or exceedance probability, PD, vis;P1 (ϵ > ϵo)A,B, (and the associated probability densities, pdf's w1(ϵ)A,B,[1]) of the envelope are obtained; (the phase is shown to be uniformly distributed in (0, 2π). These results are canonical, i.e., their analytic forms are invariant of the particular noise source and its quantifying parameter values, levels, etc. Class A interference is described by a 3-parameter model, Class B noise by a 6-parameter model.