The Rutgers SDR team: Sean Johnson, John Callinan, and Harris Ransom, recently competed in the Air Force Research Laboratories software defined radio nation-wide challenge. The Rutgers team was the only team  composed solely of undergraduate students. The team made a compelling showcase demonstrating the benefits of using machine learning over traditional algorithms for signal tracking. The team used techniques such as beam forming and time difference of arrival to provide metrics for a machine learning algorithm trained to identify a signal's position. The ML assisted techniques used managed to show a significant increase in performance from traditional methods. Due to their excellent work the team was invited to Dayton Ohio as one of the eight finalists of the competition. In Dayton the team presented their demo to a panel of judges composed of leading figures from industry and researchers from the Air Force Research Lab. On top of presenting to the panel of judges the team gave an informative presentation during an open session, followed by a live demo for the public. The team received positive feedback from ARL organizers and other attendees and looks forward to future opportunities to expand upon this research. The team completed this work from Rutgers WINLAB using equipment funded by the  DURIP #N00014-23-1-2537 grant.

The team would like to acknowledge their research advisor Professor Predrag Spasojevic of the Rutgers ECE department, Ivan Seskar of Rutgers WINLAB, Jean-Marc Sheitoyan of the Wright Brothers Institute, and Dr. Stephen Hary of the Air Force Research Laboratory for making this research a possibility.

Congratulations to Predrag, Ivan and the student team!