Electronic Thesis/Dissertation
 

Enhancement of Unidentified Radiated Emissions Identification Process Capabilities

Open Access

In the last decade, universities and the federal government have studied the use of Unintended Radiated Emissions (URE) for security applications. The published studies have shown multi-second and larger processing times, which are not suitable for many security scenarios, which require fraction of a second responses. The staggering amount of frequency spectrum data available for examination in a test object creates a processing time challenge. Additionally, as the body of electronic threats grows, along with its corresponding states or modes for each object, the database size required to store this information, threatens the practicality of a URE system in terms of required system memory and processing speeds.This research will work with an existing set of URE data (Appendix A), consisting of 166 test objects from 12 model/modes to study four URE issues related to processing speed and system growth. The research will be divided into two major parts, each part having two sections. The first section of Part I of this research will determine if the input URE data, from an unknown threat object to a threat identification system, can be reduced while the URE system maintains identification accuracy. The second section of Part I will determine if the database of the URE threat identification can be reduced in characteristic signal quantity and maintain unknown identification accuracy. The first section of Part II will use simulation to create new threat models in the URE database, to see if and how large the database can be expanded before the system fails. The second section of Part II will use simulation to expand the mode handling capability of the URE system to see how large the database can get before the system fails.

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