2021 Per Enge Early Achievement Award

Presented to: Dr. Jonathan “JR” Ryan

Citation: For developing vision-based navigation software used operationally on aircraft, UAVs, and glide munitions that provides continuous high-accuracy absolute position measurements in GPS-denied environments

Dr. Jonathan Ryan was the primary developer for the Leidos real-time aerial Vision-Based Navigation (VBN) algorithm. He performed the trade study to identify the key point and descriptor used for feature matching, and developed the tightly-coupled interface between VBN and the Particle Filter Sensor Fusion algorithm to maximize algorithm performance in areas with minimal feature content. He prototyped the algorithm in Matlab, demonstrated results in playback using data collected during flight experiments, and worked with the software engineering team to convert the algorithm to embedded C++ code. He was the flight test lead for the VBN flight experiments on the DC-3 and S-3B Viking aircraft, which included the first demonstration of a wide area search recovery following 17 minutes of flight over Lake Erie. Additionally, Dr. Ryan supported continued VBN algorithm enhancements under the DARPA SECTR program while also becoming involved in the algorithm transition to platforms for operational use.

Dr. Ryan served as the software and flight test lead as the software transitioned to additional Army, Air Force, and classified program customers for operational use including serving as technical lead for the program that led to VBN being used in theater as part of a combat mission for an Air Force manned ISR platform. Dr. Ryan led the Street Level Image Matching (SLIM) program as principal investigator where he formulated the approach and led a team of engineers who developed the deep-learning algorithm required to match live imagery to satellite-derived 3D reference models.

Dr. Ryan joined Leidos in 2013. He holds a PhD in Mechanical Engineering from Auburn University where he worked in the GAVLAB under Dr. David Bevly.