GPS sidereal filtering: coordinate- and carrier-phase-level strategies

Multipath error is considered one of the major errors affecting GPS observations. One can benefit from the repetition of satellite geometry approximately every sidereal day, and apply filtering to help minimize this error. For GPS data at 1 second interval processed using a double-difference strategy, using the day-to-day coordinate or phase residual autocorrelation determined with a 10 hour window leads to the steadiest estimates of the error-repeat lag, although a window as short as 2 hours can produce an acceptable value with >97% of the optimal lag’s correlation. We conclude that although the lag may vary with time, such variation is m...  more

Multipath error is considered one of the major errors affecting GPS observations. One can benefit from the repetition of satellite geometry approximately every sidereal day, and apply filtering to help minimize this error. For GPS data at 1 second interval processed using a double-difference strategy, using the day-to-day coordinate or phase residual autocorrelation determined with a 10 hour window leads to the steadiest estimates of the error-repeat lag, although a window as short as 2 hours can produce an acceptable value with >97% of the optimal lag’s correlation. We conclude that although the lag may vary with time, such variation is marginal and there is little advantage in using a satellite-specific or other time-varying lag in double-difference processing.
We filter the GPS data either by stacking a number of days of processed coordinate residuals using the optimum “sidereal” lag (23h 55m 54s), and removing these stacked residuals from the day in question (coordinate space), or by a similar method using double-difference phase residuals (observational space). Either method results in more consistent and homogeneous set of coordinates throughout the dataset compared with unfiltered processing. Coordinate stacking reduces geometry-related repeating errors (mainly multipath) better than phase residual stacking, although the latter takes less processing time to achieve final filtered coordinates. Thus the optimal stacking method will depend on whether coordinate precision or computational time is the over-riding criterion.