On a national level, the fields of SDS and space domain awareness (SDA) must converge in major new ways to safeguard our use of LEO. A civil space traffic management (STM) capability is being born out of the existing military capability. But with a 10-20 fold increase in civil satellites, a great deal more effort, knowledge, flexibility, and capability will be required to insure safe operations. The University of Colorado Boulder has expertise in both SDA and SDS and SWx TREC seeks to synergize these fields to attack this critical problem head on. This problem affects all of society. Thus, its solution should also involve economists, business leaders, and space law lawyers to put the growing dependence on space, and concern over impactful outcomes and adverse space events, into context.

Topics below target predicting the LEO environment, observing and tracking LEO objects, and assessing LEO disturbances through GNSS perturbations.

LEO environmental prediction

A driving need for advancing SDS is in the description and prediction of the Earth’s ionosphere, thermosphere, and magnetosphere—known as the geospace environment. This space domain encompasses the operational domain of critical satellites operating in low-Earth orbit (LEO), medium Earth orbit (MEO), and geosynchronous orbit (GEO). Varying properties of the geospace environment directly influence the performance, lifetime, and trajectory of the satellite population and the accompanying deleterious debris field. The recent emergence of satellite megaconstellations planned for LEO makes the need to predict the orbital environment particularly acute. This is because orbital perturbations that are not properly tracked and analyzed during space disturbances may lead to catastrophic collisions that render the LEO domain unusable for satellites and make launches through LEO high-risk activities.


  1. Berger, T. E., Holzinger, M. J., Sutton, E. K., & Thayer, J. P. ( 2020). Flying through uncertainty. Space Weather, 18, e2019SW002373. https://doi.org/10.1029/2019SW002373
  2. Thayer, J. P., W. K. Tobiska, M. Pilinski, and E. Sutton (2019), Remaining Issues in Upper Atmosphere Satellite Drag, Wiley AGU volume Space Weather: Contemporary Technology Impacts, A. Coster, P. Erickson, L. Lanzerotti eds. (in press, 2020)

GNSS impacts

Radio waves, such as the global navigation satellite systems (GNSS), propagating through the ionosphere will experience varying levels of refraction and scattering effects. The refraction effects result in signal group delays, carrier phase advances, and ray bending. Group delay and carrier advance introduce one of the dominant errors in the GNSS range measurements and position, velocity, and time (PVT) solutions. The signal bending is caused by gradients in ionospheric plasma density and is only noticeable for low elevation satellites which are used for radio occultation (RO) applications where the receiver is on-board a low-Earth orbiting (LEO) satellite to perform a limb-scan of GNSS signals. Scattering occurs when the signal propagates through plasma structures or irregularities which act as an irregular “lens” causing focusing and defocusing of the GNSS signals, leading to diffraction patterns at the receiver plane and ultimately variations in signal amplitude and phase, collectively referred to as ionospheric scintillation. During ionospheric scintillation, a receiver may have increased measurement errors, carrier cycle slips, and carrier tracking loops losing lock of signals.  While these ionospheric effects pose challenges for applications that require continuous and high accuracy measurements, they have enabled GNSS receivers to be utilized for passive remote sensing of the state of the ionosphere.  This subject is of interest in scientific communities studying the space environment and space weather.

This unique relationship between GNSS and the ionosphere has created an interesting inter-disciplinary field of research. In order to mitigate and forecast the ionospheric impact on GNSS, we need to have a better understanding of the ionospheric processes and states. The very adverse effects of the ionosphere on GNSS have enabled GNSS to become the most widely utilized tool for ionospheric studies. CU has established a network of ionospheric-event driven, multiple constellation GNSS data collection systems that gather signals with ionospheric disturbances. Our research team is uniquely positioned to conduct this fascinating inter-disciplinary research to advance knowledge of the ionosphere to understand its unique relationship with GNSS, to explore the potentials of GNSS in ionospheric studies, and to develop new mitigation techniques to improve GNSS PNT performances.


  1. Breitsch, B., D. Xu, Y. Morton, C. Rino, “GNSS carrier phase transitions due to ionosphere diffraction: simulation and characterization,” accepted,  IEEE Trans. Geosci. Remote Sensing, 2020.
  2. Rino, C., B. Breitsch, Y. Morton, D. Xu, C. Carrano, “GNSS signal phase, TEC, and phase scintillation,” Submitted to Navigation, J. Institute of Navigation, 2020.
  3. Yang, Z., Y. Morton, I. Zakharenkova, I. Cherniak, S. Song, W. Li, “Global view of ionospheric disturbances impacts on kinematic GPS positioning solutions during the 2015 St. Patrick’s Day storm,” accepted, J. Geophy. Res., Space Sci., 2020.
  4. Yang, Z., Y. Morton, “Low-latitude ionospheric scintillations of multi-constellation GNSS signals in relation to magnetic field orientation,” Revision under review, J. of Geodesy, 2020.
  5. Xu, D., Y. Morton, C. Rino, C. Carrano, Y. Jiao, “A two-parameter multifrequency GPS signal simulator for strong equatorial ionospheric scintillation: modeling and parameter characterization,” Navigation, J. Institute of Navigation, 67:181-195, DOI: 10.1002/navi/350, 2020.
  6. Rino, C., Y. Morton, B. Breitsch, C. Carrano, “Stochastic TEC structure characterization,” J. Geophy. Res., Space Phy., https://doi.org/10.1029/2019JA026958, 2019. 
  7. Liu, Z., Z. Yang, D. Xu, Y. J. Morton “On inconsistent ROTI derived from multi-constellation GNSS measurements of globally distributed GNSS receivers for characterizing ionospheric irregularities,” Radio Sci., 10.1029/2018RS006596, 2019. 
  8. Jiao, Y., D. Xu, C. Rino, Y. Morton, C. Carrano, “Multi-frequency GPS signal strong equatorial ionospheric scintillation simulator: algorithm, performance, and characterization,” IEEE Trans. Aero. Elec. Sys., 65(2), 263-274, DOI:10.1109/TAES.2018.2805232, 2018.
  9. Jiao, Y., C. Rino, Y. Morton, “Ionospheric scintillation simulation on equatorial GPS signals for dynamic platforms,” Navigation, J. Institute of Navigation, 65(2), 263-274, doi:10.1002/navi.231, 2018.
  10. Wang, J., Y. Morton, “Ionospheric irregularity drift velocity estimation using multi-GNSS spaced-receiver array during high latitude phase scintillation,” Radio Sci., DOI: 10.1002/2017RS006470, 2018.
  11. Xu, D., Y. Morton, “GPS navigation data bit decoding error during strong equatorial scintillation,” GPS Solutions, 22:110, https://doi.org/10.1007/s10291-018-0775-1, 2018. 
  12. Lee, J., Y. Morton, J. Lee, H-S. Moon, J. Seo, “Monitoring and mitigation of ionospheric anomalies for GNSS-based safety critical systems: A review of up-to-date signal processing techniques,” Special issue on Advances in Signal Processing for Global Navigation Satellite Systems, IEEE Signal Proc. Magazine, 34(5):96-110, DOI: 10.1109/MSP.2017.2716406, 2017. 
  13. Xu D., Y. Morton, “Semi-open loop estimation of GPS carrier phase variations during deep amplitude fading of equatorial ionospheric scintillation,” IEEE Trans. Aero. Elec. Sys., DOI: 10.1109/TAES.2017.2764778, PP(99), 2017.