Statistical modeling for the mitigation of GPS multipath delays from day-to-day range measurements
Abstract
Based on a least-squares model for double-difference GPS pseudoranges and carrier-phases, measurement residuals expressed in time series during an observation session are positively correlated between one sidereal day and the preceding days. As a result of the satellite's period, the phenomenon, which takes place at a user receiving site, is attributed to multipath interference. Examples from a weekly measurement dataset of control baselines are shown, where the known end-point coordinates also serve as a benchmark for assessing positioning accuracy. The system of error equations for mixed-model adjustment is divided into two subsystems. One set of the error equations is related to the real range measurements, while the other involves the pseudo-observation with an empirical sample variance. According to the existing correlation between day-to-day residual estimates, a multipath-mitigating algorithm is proven to improve the accuracy of the GPS height determination by at least 40%. It is also found that the algorithm depends on a variance-component estimator that adaptively scales an error covariance matrix for both the real range and empirical delay measurements.
- Publication:
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Journal of Geodesy
- Pub Date:
- April 2010
- DOI:
- 10.1007/s00190-009-0358-6
- Bibcode:
- 2010JGeod..84..223W
- Keywords:
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- GPS positioning;
- Least-squares method;
- Variance-component estimation;
- Multipath mitigation