Kalman Filtering USNO's GPS Observations for Improved Time Transfer Predictions
Abstract
The GPS Master Control Station (MCS) performs the UTC time transfer mission by uploading and broadcasting predictions of the GPS-UTC offset in subframe 4 of the GPS navigation message. These predictions are based on only two successive daily data points obtained from USNO. USNO produces these daily smoothed data points by performing a least-squares fit on roughly 38 hours worth of data from roughly 160 successive 13-minute tracks of GPS satellites. Though sufficient for helping to maintain a time transfer error specification of 28 ns (1 Sigma), the MCS's prediction algorithm does not make the best use of the available data from USNO, and produces data that can degrade quickly over prediction spans. This paper investigates how, by applying Kalman Filtering to the same available tracking data, the MCS could improve its estimate of GPS-UTC, and in particular, the GPS-UTC A(1) term. By refining the A(1) (frequency) estimate for GPS-UTC predictions, error in GPS time transfer could drop significantly. Additionally, the risk of future spikes in GPS's time transfer error could similarly be minimized, by employing robust Kalman Filtering for GPS-UTC predictions.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1995
- Accession Number
- ADA515356
Entities
People
- Steven T. Hutsell
Organizations
- 2d Space Operations Squadron