Demonstration of UAV Based GPS Jammer Localization During a Live Interference Exercise

Adrien Perkins, Louis Dressel, Sherman Lo, Tyler Reid, Kazuma Gunning, Per Enge

Abstract:	To assist in the mitigation of the effects posed by Global Navigation Satellite System (GNSS) jammers, this paper demonstrates the use of an unmanned aerial vehicle (UAV) capable of autonomously localizing the source of Global Positioning System (GPS) jamming in a live jamming exercise hosted by the Department of Homeland Security (DHS). Developing an autonomous UAV for jammer localization in a real-world environment needs to address three main challenges: accurate measurements of the jamming signal, rapid localization steps and reliable navigation in the presence of interference. Our system, Jammer Acquisition with GPS Exploration and Reconnaissance (JAGER), has been developed to address those main challenges for rapid localization and has been previously tested with localizing Wi-Fi signals. This paper outlines the modifications to JAGER required to be able to move from localizing Wi-Fi sources to localizing GPS jammers. Modifications include new sensing equipment for determining the bearing to the jammer and additional navigation systems to fly while the jammer is active. The main goal for the testing was to demonstrate the feasibility of JAGER to localize a GPS jammer at realistic distances and the performance of several different localization methods. The second goal was to explore possible GPS-denied navigation solutions.
Published in:	Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016) September 12 - 16, 2016 Oregon Convention Center Portland, Oregon
Pages:	3094 - 3106
Cite this article:	Perkins, Adrien, Dressel, Louis, Lo, Sherman, Reid, Tyler, Gunning, Kazuma, Enge, Per, "Demonstration of UAV Based GPS Jammer Localization During a Live Interference Exercise," Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016), Portland, Oregon, September 2016, pp. 3094-3106. https://doi.org/10.33012/2016.14661
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