Abstract
The Fractional Cycle Bias (FCB) product is crucial for the Ambiguity Resolution (AR) in Precise Point Positioning (PPP). Different from the traditional method using the ionospheric-free ambiguity which is formed by the Wide Lane (WL) and Narrow Lane (NL) combinations, the uncombined PPP model is flexible and effective to generate the FCB products. This study presents the FCB estimation method based on the multi-Global Navigation Satellite System (GNSS) precise satellite orbit and clock corrections from the international GNSS Monitoring and Assessment System (iGMAS) observations using the uncombined PPP model. The dual-frequency raw ambiguities are combined by the integer coefficients (4,− 3) and (1,− 1) to directly estimate the FCBs. The details of FCB estimation are described with the Global Positioning System (GPS), BeiDou-2 Navigation Satellite System (BDS-2) and Galileo Navigation Satellite System (Galileo). For the estimated FCBs, the Root Mean Squares (RMSs) of the posterior residuals are smaller than 0.1 cycles, which indicates a high consistency for the float ambiguities. The stability of the WL FCBs series is better than 0.02 cycles for the three GNSS systems, while the STandard Deviation (STD) of the NL FCBs for BDS-2 is larger than 0.139 cycles. The combined FCBs have better stability than the raw series. With the multi-GNSS FCB products, the PPP AR for GPS/BDS-2/Galileo is demonstrated using the raw observations. For hourly static positioning results, the performance of the PPP AR with the three-system observations is improved by 42.6%, but only 13.1% for kinematic positioning results. The results indicate that precise and reliable positioning can be achieved with the PPP AR of GPS/BDS-2/Galileo, supported by multi-GNSS satellite orbit, clock, and FCB products based on iGMAS.
Highlights
Precise Point Positioning (PPP) Ambiguity Resolution (AR) is important to obtain the positioning accuracy at centimeter-level in a short time at a station (Bisnath and Gao 2008; Wang et al 2019)
The uncombined PPP model is adopted to generate the Fractional Cycle Bias (FCB) with the final satellite orbit and clock corrections with Global Positioning System (GPS), Galileo, and BeiDou-2 Navigation Satellite System (BDS-2) observations at the BeiDou analysis and service center of Chang’an University, which is a member of the international GNSS Monitoring and Assessment System (iGMAS)
To achieve the fast and precise single station positioning service, the PPP AR technique is the key to speed up the positioning bias convergence and improve the accuracy
Summary
Precise Point Positioning (PPP) Ambiguity Resolution (AR) is important to obtain the positioning accuracy at centimeter-level in a short time at a station (Bisnath and Gao 2008; Wang et al 2019). Due to the Fractional Cycle Biases (FCBs) in phase measurements which are assimilated into the undifferenced ambiguities in PPP, the integer properties of the estimated ambiguities are lost (Gabor and Nerem 1999). Based on an empirical assumption that the Uncalibrated Phase Delays (UPD) are relatively stable in time, the SingleDifference (SD) FCBs of the Wide Lane (WL) and Narrow Lane (NL) float ambiguities between satellites are estimated from a reference network (Ge et al 2008). Due to the short wavelength of the narrow-lane ambiguity, for instance, about 10 cm for Global Positioning System (GPS), the NL FCBs are not as stable as the WL, which are proposed to estimate 15 min mean values
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