On-Orbit GNSS SV Time Management: Automated Time Projection and Control
Travis Driskell, L3Harris Technologies
Location: Seaview A/B
Date/Time: Thursday, Jan. 30, 2:35 p.m.
GPS nanosecond-level time accuracy is limited by the fixed bit structure of the legacy navigation message (LNAV) defined in the IS-GPS-200 that provides the space vehicle’s (SV) clock correction phase, frequency, and frequency drift states. Due to the intrinsic frequency drift of the Rubidium Atomic Frequency Standards (RAFS) used in today’s GPS satellites, time error slowly accumulates over time and deviates onboard SV time from GPS time. Clock correction uploads estimated by the control segment Kalman filter are routinely provided to each SV and broadcasted to users to correct for the day-to-day time errors and synchronize to GPS time. However, if the SV time offset exceeds the LNAV clock correction upload limit, then the SV will broadcast inaccurate clock corrections and degrade GPS user performance. Therefore, it is imperative to monitor SV clock offset from GPS time and perform onboard clock frequency drift adjustments to maintain the SV clock offset within the LNAV clock correction upload limits while providing continuous and uninterrupted SV operation.
To that end, we developed an SV clock monitoring and analysis tool that estimates current and projects future SV clock offsets and autonomously derives optimal SV clock adjustments for frequency and frequency drift to steer phase and frequency to within clock correction upload limits. In this paper, we will demonstrate our tool utilizing the publicly available National Geospatial-Intelligence Agency (NGA) GPS Precise Ephemeris data. First, we will derive the IS-GPS-200 LNAV clock correction limits with respect to GPS time. Then we will apply our tool to estimate and project SV clock states using the NGA data and introduce our minimization algorithm used to compute the recommended SV clock adjustments to steer SV time within the LNAV clock correction upload limits. Finally, we will demonstrate the algorithm using clock data of a newly powered on RAFS to exemplify how we can optimally maintain SV time with the RAFS’s beginning-of-life, nonlinear frequency drift.
Disclaimer: “The views expressed are those of the authors and do not reflect the official guidance or position of the United States Government, the Department of Defense the United States Air Force or the United States Space Force.”