2015 Fellow

Presented to: Dr. Attila Komjathy

Citation: For contributions to remote sensing of Earth’s
ionosphere using GNSS signals.

Dr. Attila Komjathy has made foundational contributions to the art and science of navigation through his research on ionospheric remote sensing and applications of GNSS signals. He is the manager and technical lead for the Jet Propulsion Laboratory’s deliveries of GPS satellite differential hardware bias values to the US Air Force. Dr. Komjathy was instrumental in the design of the GPS Next Generation Control System (OCX) algorithms.

Dr. Komjathy is the technical lead for the design and implementation of algorithms that provide high-accuracy ionospheric delay estimates for NASA’s Deep Space Tracking Network. His GPS expertise led to key roles in NASA’s Phoenix mission design and navigation team, and NASA’s Mars Science Laboratory (MLS) operations team. He was responsible for time-critical ionospheric calibration measurements during the entry-descentlanding phase of MSL in 2013. He has generated GPS and GLONASS-based ionospheric products used by various government agencies. Recently, his research has turned toward developing new technologies to detect ionospheric signatures of natural hazards such as earthquakes, volcanoes, and tsunamis using ground based and spaceborne GNSS measurements, which has the potential to augment early warning systems, save human lives, and significantly reduce adverse economic consequences of natural hazards.

Dr. Komjathy received the GPS World 2013 Leadership Award, two NASA Space Act Awards, and several NASA Group Achievement Awards. He has been a member of the FAA’s WAAS Integrity Performance Panel for over 10 years and is a key technical contributor to Satellite-Based Augmentation Systems (SBAS). He received his PhD from the University of New Brunswick and worked as a postdoctoral researcher at the University of Colorado at Boulder before joining the Jet Propulsion Laboratory in 2001. He has written widely cited papers on ionospheric remote sensing with GNSS and on the use of reflected GNSS signals to estimate soil moisture, ocean wind speed and direction, and properties of ice.