|Student Name:||2Lt Angie Zeqollari|
|Thesis:||Ultra-Wideband Radio Frequency Fingerprinting|
|Location:||ENY Conference Room|
|Attendance Restrictions:||Limited Distribution|
|Date & Time:||02/14/2014 at 1300|
|Abstract:|| The AFIT Noise Radar Network (NoNET) has demonstrated capabilities in many standard radar functions to include multistatic imaging and indoor navigation. Radio Frequency (RF) fingerprinting is a technology that exploits the unique characteristics of RF signatures in order differentiate between unknown devices. RF fingerprinting to this point has relied on a radar receiver with an narrow instantaneous bandwidth. This research aims to combine RF fingerprinting techniques with the ultrawideband (UWB) signal produced by the NoNET to provide a proof of concept demonstration of RF fingerprinting capabilities utilizing an ultra-wideband signal. Results demonstrate the potential benefits of this approach to RF fingerprinting classification.