RF Coupling Revisited
Abstract
Electromagnetic weapons in the radiofrequency range (700-MHz to 95-GHz) at on-target powerdensities that induce tenths- to ones-of-"volts onto a printed circuit board trace, free wire, or otherintegrated circuit input (hereafter high-power microwaves or HPM) repr"esent a single event effect(SEE) threat to microelectronics and their downstream applications [1-4]. Developing a deeperunderstand"ing of the means by which HPM couple to wires, traces, chasses, integrated circuits,and/or their enclosures, as a function of the s""ource properties, is the objective of this proposedeffort. A stretch objective is to further understand the secondary and tertiary"" coupling effects,including direct and inductive coupling. At the conclusion of this work, the vision is a balance ofempirical- an""d simulation-derived results that will drive a generally applicable and pragmaticmodel (i.e., rules-of-thumb) that may be used info"rm both the offensive and defensive side of HPMdesign and electronics and their enclosures.Since at least the mid-1960s through to"day, electronic warfare ~ and to a lesser extent HPM ~testing has been a staple for what is now MIL STD 464C. Empirical testing has"" and will likelycontinue to be used as there is no current ability to generate sufficient (i.e., simple, but mostlyaccurate) model"s. This effects testing has been employed against assets ranging from motorvehicles to desktop computers to unmanned aerial vehicle"s to smart phones to instrument landingsystems. While with enough detail and empirical feedback data, some models have been develop""ed[5,6], the models are not generalizable. Of those models that seek to be generalizable, they are toocomplex to setup, inaccurate"" and/or ill-pragmatic. A new approach, which stands on the shouldersof this previous work, but harnesses the utility/power of new c""apabilities is needed.New capabilities, whose confluence will take the above work to a new level, include the ability to:(a) map o""r predict the three-dimensional layout of complex electrical structures (e.g., wiringharness but not necessarily multilayer printed" circuit boards); (b) automatically transfer thephysical maps into simulation; (c) automatically approximate the complexpermittivity/permeability of the materials; (d) run multi-source-parameter permutations onsupercomputers inexpensively (through the ability to parallelize and run on an order-of-magnitudemore cores/memory than two years earlier); (e) validate simulations through automated" empiricalmeasurements; and, (f) most of all, use machine learning methods to extract trends that the humanscannot.In this work,"" we will design, build and test, an empirical measurement and simulation systemcapable of demonstrating the new capabilities descri"bed above in an effort to develop a predictivecapability that is both simple and accurate enough to be useful for HPM effects and design needs.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 29, 2017
- Source ID
- N000141712932
Entities
People
- Anthony N. Caruso
Organizations
- Office of Naval Research
- United States Navy
- University of Missouri System