Estimation of QZSS differential code biases using QZSS/GPS combined observations from MGEX

As an important error source in Global Navigation Satellite System (GNSS) positioning and ionospheric modeling, the differential code biases (DCB) need to be estimated accurately, e.g., the regional Quasi-Zenith satellite system (QZSS). In this paper, the DCB of QZSS is estimated by adopting the global ionospheric modeling method based on QZSS/GPS combined observations from Multi-GNSS experiment (MGEX). The performance of QZSS satellite and receiver DCB is analyzed with observations from day of year (DOY) 275–364, 2018. Good agreement between our estimated QZSS satellite DCB and the products from DLR and CAS is obtained. The bias and root mean square (RMS) of DCB are mostly within ±0.3 ns. The day-to-day fluctuation of the DCB time series is less than 0.5 ns with about 96% of the cases for all satellites. However, the receiver DCB is a little less stable than satellite DCB, and their standard deviations (STDs) are within 1.9 ns. The result shows that the stability of the receiver DCBs is not significantly related to the types of receiver or antenna.     

Extending multipath hemispherical model to account for time-varying receiver code biases

Multipath effects on code observables account for one of the major error sources in high-accuracy Global Positioning System (GPS)-based positioning, atmosphere sounding and timing applications. The multipath hemispherical model (MHM) represents one of the most widely used methods of mitigating code multipath effects by taking advantage of their spatial repeatability. The use of MHM usually assumes that the receiver code biases (RCBs) are time-invariant; however, this assumption is not always valid, as RCBs and linear combinations thereof (differential code biases, for instance) have long been found to be time-varying over a period of one day. In this contribution, we propose an extended multipath hemispherical model (EMHM) that is capable of mitigating the code multipath effects in the presence of time-varying RCBs. Consequently, the proposed EMHM has two advantages. First, the EMHM gives rise to code multipath corrections with improved reliability because it addresses the intraday variability of RCBs. Second, more interestingly, the EMHM allows easy and effective calibration of short-term temporal variations, if any, in the RCB on each frequency. These advantages are hopeful to benefit GPS code-related applications.     

Correction model of BDS satellite-induced code bias and its impact on precise point positioning

There are code biases on the pseudo-range observations of the Beidou Navigation Satellite System (BDS) that range in size from several decimeters to larger than one meter. These biases can be divided into two categories, which are the code biases in the pseudo-range observations of Inclined Geo-Synchronous Orbit (IGSO) satellites and Medium Earth Orbit (MEO) satellites and the code biases in the pseudo-range observations of Geosynchronous Earth Orbit (GEO) satellites. In view of the code bias of the IGSO/MEO satellites, the code bias correction model is established using the weighted least square curve fitting method. After the correction, the code biases of the IGSO and MEO satellites are clearly mitigated. A methodology of correcting GEO code bias is proposed based on the empirical mode decomposition (EMD)-wavelet transform (WT) coupled model. The accuracies of the GEO multipath combination of the B1, B2 and B3 frequencies are improved by 39.9%, 17.9%, and 29.4%, respectively. Based on the corrections above, the ten days observations of three Multi-GNSS Experiment (MGEX) stations are processed. The results indicate that the convergence time of the precise point positioning (PPP) can be improved remarkably by applying a code bias. The mean convergence time can be improved by 14.67% after the IGSO/MEO code bias correction. By applying the GEO code bias, the mean convergence time can be further improved by 17.42%.     

A real-time ionospheric model based on GNSS Precise Point Positioning

This paper proposes a method of real-time monitoring and modeling the ionospheric Total Electron Content (TEC) by Precise Point Positioning (PPP). Firstly, the ionospheric TEC and receiver’s Differential Code Biases (DCB) are estimated with the undifferenced raw observation in real-time, then the ionospheric TEC model is established based on the Single Layer Model (SLM) assumption and the recovered ionospheric TEC. In this study, phase observations with high precision are directly used instead of phase smoothed code observations. In addition, the DCB estimation is separated from the establishment of the ionospheric model which will limit the impacts of the SLM assumption impacts. The ionospheric model is established at every epoch for real time application. The method is validated with three different GNSS networks on a local, regional, and global basis. The results show that the method is feasible and effective, the real-time ionosphere and DCB results are very consistent with the IGS final products, with a bias of 1–2 TECU and 0.4 ns respectively.     

Analysis of GNSS clock prediction performance with different interrupt intervals and application to real-time kinematic precise point positioning

Continuous and timely real-time satellite orbit and clock products are mandatory for real-time precise point positioning (RT-PPP). Real-time high-precision satellite orbit and clock products should be predicted within a short time in case of communication delay or connection breakdown in practical applications. For prediction, historical data describing the characteristics of the real-time orbit and clock can be used as the basis for performing the prediction. When historical data are scarce, it is difficult for many existing models to perform precise predictions. In this paper, a linear regression model is used to predict clock products. Seven-day GeoForschungsZentrum (GFZ) final clock products sampled at 30 s are used to analyze the characteristics of GNSS clocks. It is shown that the linear regression model can be used as the prediction model for the satellite clock products. In addition, the accuracy of the clock prediction for different satellites are analyzed using historical data with different periods (such as 2 and 10 epochs). Experimental results show that the accuracy of the clock with the linear regression prediction model using historical data with 10 epochs is 1.0 ns within 900 s. This is higher accuracy than that achieved using historical data of 2 epochs. Finally, the performance analysis for real-time kinematic precise point positioning (PPP) is provided using GFZ final clock prediction results and state space representation (SSR) clock prediction results when communication delay or connection breakdown occur. Experimental results show that the positioning accuracy without prediction is better than that with prediction in general, whether using the final clock product or the SSR clock product. For the final clock product, the positioning accuracy in the north (N), east (E), and up (U) directions is better than 10.0 cm with all visible GNSS satellites with prediction. In comparison, the 3D positioning accuracy of N, E, and U directions with visible GNSS satellites whose prediction accuracy is better than 0.1 ns using historical data of 10 epochs is improved from 15.0 cm to 7.0 cm. For the SSR clock product, the positioning accuracy of N, E, and U directions is better than 12.0 cm with visible GNSS satellites with prediction. In comparison, the 3D positioning accuracy of N, E, and U directions with visible GNSS satellites whose prediction accuracy is better than 0.1 ns using historical data of 10 epochs is improved from 12.0 cm to 9.0 cm.