Traditional Precise Point Positioning Research Articles

Improving GNSS PPP Performance in the South China Under Different Weather Conditions by Using the Weather Research and Forecasting (WRF) Model‐Derived Wet Delay Corrections

AbstractAtmospheric wet delay caused by Precipitable Water Vapor (PWV) significantly impacts the performance of many geodetic surveying systems such as Global Navigation Satellite System (GNSS). In this study, we use wet delay corrections forecast by the Weather Research and Forecasting (WRF) model to enhance GNSS Precise Point Positioning (PPP) during two observation periods with two different weather conditions, that is, period 1: March 01 to 14, 2020 (average PWV: 23.5 kg/m2) and period 2: June 02 to 15, 2020 (flooding weather with average PWV: 55.6 kg/m2), over the South China. PWV data from 277 to 263 GNSS stations are assimilated into WRF model to enhance the WRF water vapor forecasting capability for period 1 and period 2, respectively. Wet delay corrections from two different WRF configurations, that is, WRF no data assimilation and WRF with assimilation of GNSS PWV, are used to augment the PPP. Totally, eight WRF‐enhanced PPP schemes are tested. The results show that WRF‐enhanced PPP schemes generally have a better positioning performance in the up component than traditional PPP. After using WRF wet delay corrections, for static mode, the vertical positioning accuracy is improved by 14.6% and 33.7% for period 1 and period 2, respectively. The corresponding convergence time are reduced by 41.8% and 25.0% for period 1 and period 2, respectively. For kinematic mode, the positioning accuracy improvements in the up component reach 13.8% and 19.0% for period 1 and period 2, respectively. The kinematic PPP convergence time is reduced by up to 8.2% for period 1.

An Interstation Undifferenced Real-Time Time Transfer Method with Refined Modeling of Receiver Clock

Due to their advantages of high measurement accuracy and wide coverage, global navigation satellite systems (GNSSs) can carry out long-distance time transfers, among which the precise point positioning (PPP) method is widely used. However, the accuracy and stability of PPP real-time time transfer are restricted by the real-time satellite clock offset products. In addition, the receiver clock offset is usually estimated using the white noise model, which ignores the correlation of the clock offsets between adjacent epochs and the stability of the atomic clock itself. In order to obtain higher performance time transfer results, we propose an interstation undifferenced time transfer method with refined modeling of the receiver clock. This method takes the satellite clock offset as the parameter to be estimated, which can avoid the influence of external satellite clock offset products. In addition, the refined modeling of the receiver clock can improve the strength of the model and the accuracy of time transfer. Based on the ultrarapid satellite orbit products provided by the International GNSS Service (IGS), time transfer experiments are carried out using data from IGS observatories and self-collected data. The results show that sub-nanosecond accuracy can be achieved in real-time time transfer using this method. Compared with the traditional PPP model, the accuracies of the four time links are increased by 88.4%, 92.9%, 88.6%, and 74.5%, respectively, and the stability is increased by approximately 66.4% on average. Moreover, after applying the clock offset constraint model, frequency stability is further improved, in which the short-term stability is improved significantly, with a maximum of 86.9% and an average improvement of approximately 66.8%.

Investigation of the capability of multi-GNSS PPP-AR method in detecting permanent displacements

The traditional-precise point positioning (PPP) technique may provide a positioning as precise as the relative positioning technique in long-term observation durations. However, since it cannot provide high-precision positioning due to ambiguity problem in short-term observations, the interest in the PPP-AR (Ambiguity Resolution) technique has increased. The main purpose of this study is to investigate the performance of traditional-PPP and PPP-AR techniques for monitoring permanent displacements, considering different observation durations based on different satellite combinations. For this purpose, a displacement simulator that can move precisely in one direction and in the horizontal plane over a small distance was used. 6 different displacements were simulated, and all collected GNSS observations were evaluated with traditional-PPP, PPP-AR, and relative methods. Moreover, these methods were examined by considering the Global Positioning System (GPS), European Global Navigation Satellite System (Galileo), and GPS/Galileo satellite combinations. The findings clearly demonstrated the superiority of the PPP-AR technique outperformed the traditional-PPP technique in short-term observation durations and emphasize the contribution of multi-GNSS (Global Navigation Satellite System) combinations to both methods.

Properties of multi-GNSS uncalibrated phase delays with considering satellite systems, receiver types, and network scales

The Wide-Lane (WL) and Narrow-Lane (NL) Uncalibrated Phase Delays (UPDs) are the prerequisites in the traditional Precise Point Positioning (PPP) Ambiguity Resolution (AR). As the generation mechanism of various biases becomes more complex, we systematically studied the impact factors of four satellite systems WL and NL UPDs from the perspective of parameter estimation. Approximately 100 stations in a global network are used to generate the UPDs. The results of different satellite systems show that the estimation method, update frequency, and solution mode need to be treated differently. Two regional networks with different receiver types, JAVAD, and Trimble, are also adopted. The results indicate that the receiver-dependent bias has an influence on UPD estimation. Also, the hardware delays can inhibit the satellite-side UPDs if these receiver-specific errors are not fully deployed or even misused. Furthermore, the temporal stability and residual distribution of NL UPDs are significantly enhanced by utilizing a regional network, with the improvements by over 68% and 40%, respectively. It demonstrates that different network scales exhibit the different implication of unmodeled errors, and the unmodeled errors cannot be ignored and must be handled in UPD estimation.

A new receiver clock model to enhance BDS-3 real-time PPP time transfer with the PPP-B2b service

A new Precise Point Positioning (PPP) service, called the PPP-B2b service, has been implemented in the BeiDou-3 Navigation Satellite System (BDS-3), which brings new opportunities for time transfer. However, the solution using the traditional PPP method with the PPP-B2b correction still absorbs some unknown errors and needs reconverging when there exist abnormal data. We developed a new receiver clock model to improve PPP time transfer using the PPP-B2b correction. The traditional PPP time transfers using PPP-B2b with BDS-3, Global Positioning System (GPS), and BDS-3/GPS (Scheme1) are compared with the corresponding time transfer with the proposed clock model (Scheme2). The results show that GPS-only PPP is not recommended because of low accuracy of 2 ns. BDS-3 or BDS-3/GPS PPP time transfers in Scheme1 can realize about 0.2 ns accuracy. When the new clock model is applied, the accuracy can be improved by up to 45% and 39.8% for BDS-3 and BDS-3/GPS PPP, respectively. The proposed clock model can significantly improve the short-term frequency stability by 57.4%, but less for the long-term stability.

Integrity monitoring scheme for undifferenced and uncombined multi-frequency multi-constellation PPP-RTK

The precise point positioning (PPP)-based real-time-kinematic (RTK) method attracts increasing attention from both academia and industry because of its potential for high accuracy positioning with a shorter convergence time compared to the traditional PPP. Besides high accuracy, integrity monitoring (IM) is indispensable for safety–critical real-time land vehicle and aviation applications. As the traditional advanced receiver autonomous integrity monitoring (ARAIM) method is designed for (smoothed) pseudorange-based positioning, the complexity of multi-frequency multi-constellation PPP-RTK using carrier phase measurements has not been given sufficient consideration. This study proposes an IM scheme for multi-frequency multi-constellation uncombined PPP-RTK applying the ARAIM theory, with a new comprehensive threat model to accommodate not only pseudorange measurements, but also carrier phase measurements, and other fault events arising from the network corrections that support PPP-RTK. Characteristics of different types of faults are analyzed with the aid of numerical experiments. In addition, the impact of ambiguity-fixed solutions on PPP-RTK integrity performance is investigated. The authors have also conducted case studies, including static and real-kinematic positioning experiments. Experiments have demonstrated that fast convergence in accuracy and the position error bounds, or protection levels, with a given integrity risk, in horizontal position components of PPP-RTK could be achieved. For the open sky environments on a highway, the protection levels estimated by PPP-RTK solutions have the potential to meet the alert limit requirement for road transportation using ambiguity-fixed PPP-RTK positioning under the assumption that the risks of wrong ambiguity fixing are very small and can be ignored.

BDS PPP-IAR: Apply and assess the satellite corrections from different regional networks

BeiDou Navigation Satellite System (BDS) has contributed to, extended, and densified the concept of satellite navigation since its first generation. Although the traditional precise point positioning (PPP) technique has been gradually replaced by its successor, that is, PPP-IAR by means of integer ambiguity resolution, most of the current studies regarding BDS-only positioning are only in the scientific sense and thus lack the feasibility of implementing PPP-IAR in societal applications. This is because building up a global or a large regional network with hundreds of reference stations is less realistic for small- and medium-sized enterprises. This manuscript aims to bridge the gap between scientific research and societal applications and thereby expand the BDS commercial services to various fields of navigation, positioning and timing. Three regional networks with the approximate distances of 470km, 1100km, and 1700km in Eastern Asia are selected, and each network contains no more than 15 reference stations and 5 user stations. First, the satellite-related corrections generated from individual networks are compared to each other, and the results show that the differences of satellite clock corrections vary from 0.1 to 0.15m, whereas those of satellite phase delay corrections vary from 0.39 to 0.53m. Then, users apply the satellite corrections not only from their own network but from the other two networks to verify if these corrections are interchangeable between different networks because it would be meaningful for improving the robustness and integrity of the positioning services once these corrections can be backups for each other. The results show that the ambiguity fixed kinematic positioning can always achieve centimeter accuracy level; however, ambiguity wrong fixing problems may appear when a user applies another network’s corrections. Besides, users may expect an 8.5min time span to achieve a centimeter-accuracy level if they apply the satellite corrections from their own network. Though it is well known that not so much the number of epochs but the change of geometry that contributes to the determination of the positions, a high sampling rate does speed up ambiguity fixing by means of a large number of observations within a short period. The experiments of 1s interval indicate that the convergence time of centimeter level positioning accuracy can be reduced to 2min under some conditions.

Performance Assessment of PPP-AR Positioning and Zenith Total Delay Estimation with Modernized CSRS-PPP

Abstract The precise point positioning (PPP) method has become more popular due to powerful online global navigation satellite system (GNSS) data processing services, such as the Canadian Spatial Reference System-PPP (CSRS-PPP). At the end of 2020, the CSRS-PPP service launched the ambiguity resolution (AR) feature for global positioning system (GPS) satellites. More reliable results are obtained with AR compared to the results with traditional ambiguity-float PPP. In this study, the performance of the modernized CSRS-PPP was comparatively assessed in terms of static positioning and zenith total delay (ZTD) estimation. Data for 1 month in the year 2019 obtained from 47 international GNSS service (IGS) stations were processed before and after modernization of the CSRS-PPP. The processes were conducted for GPS and GPS + GLONASS (GLObalnaya NAvigatsionnaya Sputnikovaya Sistema) satellite combinations. Besides, the results were analyzed in terms of accuracy and convergence time. According to the solutions, the AR feature of the CSRS-PPP improved the accuracy by about 50% in the east component for GPS + GLONASS configuration. The root-mean-square error (RMSE) of the ZTD difference between modernized CSRS-PPP service and IGS final troposphere product is 5.8 mm for the GPS-only case.

Improving the Performance of Time-Relative GNSS Precise Positioning in Remote Areas.

Global navigation satellite systems (GNSS) can attain centimeter level positioning accuracy, which is conventionally provided by real-time precise point positioning (PPP) and real-time kinematic (RTK) techniques. Corrections from the data center or the reference stations are required in these techniques to reduce various GNSS errors. The time-relative positioning approach differs from the traditional PPP and RTK in the sense that it does not require external real-time corrections. It computes the differences in positions of a single receiver at different epochs using phase observations. As the code observations are not used in this approach, its performance is not affected by the noise and multipath of code observations. High reliability is another advantage of time-relative precise positioning because the ambiguity resolution is not needed in this approach. Since the data link is not required in the method, this approach has been widely used in remote areas where wireless data link is not available. The main limitation of time-relative positioning is that its accuracy degrades over time between epochs because of the temporal variation of various errors. The application of the approach is usually limited to be within a time interval of less than 20 min. The purpose of this study was to increase the time interval of time-relative positioning and to extend the use of this method to applications with a longer time requirement, especially in remote areas without wireless communication. In this paper, the main error sources of the time-relative method are first analyzed in detail, and then the approach to improve the accumulated time relative positioning method is proposed. The performance of the proposed method is assessed using both static and dynamic observations with a duration as long as several hours. The experiments presented in this paper show that, among the four scenarios tested (i.e., GPS, GPS/Galileo, GPS/Galileo/BeiDou, and GPS/Galileo/BeiDou/GLONASS), GPS/Galileo/BeiDou performed best and GPS/Galileo/BeiDou/GLONASS performed worst. The maximum positioning errors were mostly within 0.5 m in the horizontal direction, even after three hours with GPS/Galileo/BeiDou. It is expected that the method could be used for positioning and navigation for as long as several hours with decimeter level horizontal accuracy in remote areas without wireless communication.

Investigating Performance of High-Rate GNSS-PPP and PPP-AR for Structural Health Monitoring: Dynamic Tests on Shake Table

AbstractThis paper investigates the usability of Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) methods, traditional PPP with a float-ambiguity solution and with ambiguit...

Ionosphere-Constrained Single-Frequency PPP with an Android Smartphone and Assessment of GNSS Observations.

With the development of Global Navigation Satellite System (GNSS) and the opening of Application Programming Interface (API) of Android terminals, the positioning research of Android terminals has attracted the attention of GNSS community. In this paper, three static experiments were conducted to analyze the raw GNSS observations quality and positioning performances of the smartphones. For the two experimental smartphones, the numbers of visible satellites with dual-frequency signals are unstable and not enough for dual-frequency Precise Point Positioning (PPP) processing all through the day. Therefore, the ionosphere-constrained single-frequency PPP model was employed to improve the positioning with the smartphones, and its performance was evaluated and compared with those of the Single Point Positioning (SPP) and the traditional PPP models. The results show that horizontal positioning accuracies of the smartphones with the improved PPP model are better than 1 m, while those with the SPP and the traditional PPP models are about 2 m.

Precision point positioning with additional baseline vector constraint

Abstract Traditional precise point positioning (PPP) based on undifferenced ionosphere-free linear combination of observations has many advantages such as high accuracy and easy operation. PPP usually uses the Kalman Filter (KF) to estimate state vector. However, the positioning performance depends on the accuracy of the kinematic model and initial value. The inaccurate kinematic model or initial value will lead to filter performance degradation or even divergence. To overcome this problem, this paper proposes a PPP method with an additional baseline vector constraint, which uses the direction information and length information of the baseline to correct the estimated position of the receiver. By reducing the error covariance matrix of the float solution, the algorithm improves the accuracy of the float solution. By using the collected real GPS static and kinematic data, the performance of the traditional model and the proposed model in this paper are compared. It is shown that the additional baseline vector constraint improves the PPP solution effectively in comparison with that of traditional PPP model. Additionally, the contribution of the additional constraint is up to the accuracy of the prior information.

Reducing convergence time of precise point positioning with ionospheric constraints and receiver differential code bias modeling

Long convergence time has limited the wide application of traditional precise point positioning (PPP) based on an ionosphere-free combination of dual-frequency observations. Different from the traditional PPP, the uncombined PPP method based on raw observations estimates ionospheric delays. When external ionospheric information is available, it can be applied as a constraint to help shorten the convergence time, as a result of the reduced correlation between the position and the ionospheric parameters. The receiver differential code biases (DCBs) will be a concern, however, when applying the external ionospheric information. For receiver DCBs, it is usually assumed that the biases can be absorbed by the receiver clock parameters. We have demonstrated that the receiver DCBs cannot be fully assimilated by one receiver code clock parameter because the receiver DCBs have different effects on the code and carrier phase measurements at any frequency. Additional parameters are necessary to model the receiver DCBs so that their effects on the positioning solution can be minimized. We developed an ionosphere-constrained PPP model to incorporate ionospheric total electron content (TEC) in the slant (STEC) and vertical (VTEC) when leveraging a regional network and global ionospheric maps (GIMs). Both static and kinematic experimental results show that the convergence time and the positioning accuracy can be improved significantly. Accuracies at the first epoch of 0.4 m for GIM constraints, and 0.2 m for the regional constraints, are achievable. The convergence time to 1 dm horizontal accuracy is reduced to 7.5 min at a 68% confidence level.

GPS and BDS combined PPP model with inter-system differenced observations

This study proposes a combined precise point positioning (PPP) model, called the inter-system differenced PPP model, in which it formed the satellite-differenced observation between different satellite systems. Compared with the traditional combined PPP model, the inter-system differenced PPP model has the following characteristics: (1) The satellite difference between various systems can eliminate the receiver clock bias parameter, it enhances the strength of the PPP model. (2) Inter-satellite differences can eliminate some common model errors and reduce the impact of observation errors. (3) The system time difference can be calculated directly to provide the basis for time offset monitoring. In order to verify the positioning results of the inter-system differenced model, static PPP and dynamic PPP experiments were carried out to test the positioning accuracy and convergence time, and the results were compared with those of the traditional combination PPP model. In addition, the offset characteristics introduced by the inter-system differenced model were analysed, and the optimal estimation strategy was determined by dynamic PPP tests. Preliminary results are as follows: (1) For inter-system differenced static PPP, the convergence time of stations is less than 20 min. The standard deviation (STD) of the position bias for the East (E), North (N), and Up (U) components are better than 2.5 cm, 1.0 cm and 3.0 cm, respectively, and the corresponding root mean square deviation (RMS) are better than 3.0 cm, 1.5 cm and 6.0 cm, respectively. Compared with the traditional combined PPP model, the average convergence time of the inter-system differenced model is nearly the same, but its overall positioning accuracy is better. (2) For the inter-system differenced dynamic PPP model, the convergence time of stations is better than 30 min. The STD of the position bias for the E, N, and U components is better than 3.0 cm, 2.0 cm and 4.5 cm respectively, and the RMS is better than 4.0 cm, 2.5 cm and 7.0 cm respectively. Compared with the traditional combined PPP model, the convergence of the inter-system differenced model is slightly better, and the positioning accuracy does not differ significantly. Moreover, the inter-system differenced model is much better than the traditional model when fewer satellites are available. (3) The offset between GPS and BDS corresponding with the precise products of GFZ is related to the type of receiver, and the daily standard of offset is less than 0.5 ns. In addition, we determined optimum process noise of the offset parameter to be a 10-3/3(m2/s) random walk after comparing several options.

Performance of Selected Ionospheric Models in Multi-Global Navigation Satellite System Single-Frequency Positioning over China

Ionospheric delay as the major error source needs to be properly handled in multi-GNSS (Global Navigation Satellite System) single-frequency positioning and the different ionospheric models exhibit apparent performance difference. In this study, two single-frequency positioning solutions with different ionospheric corrections are utilized to comprehensively analyze the ionospheric delay effects on multi-frequency and multi-constellation positioning performance, including standard point positioning (SPP) and ionosphere-constrained precise point positioning (PPP). The four ionospheric models studied are the GPS broadcast ionospheric model (GPS-Klo), the BDS (BeiDou Navigation Satellite System) broadcast ionospheric model (BDS-Klo), the BDS ionospheric grid model (BDS-Grid) and the Global Ionosphere Maps (GIM) model. Datasets are collected from 10 stations over one month in 2019. The solar remained calm and the ionosphere was stable during the test period. The experimental results show that for single-frequency SPP, the GIM model achieves the best accuracy, and the positioning accuracy of the BDS-Klo and BDS-Grid model is much better than the solution with GPS-Klo model in the N and U components. For the single-frequency PPP performance, the average convergence time of the ionosphere-constrained PPP is much reduced compared with the traditional PPP approach, where the improvements are of 11.2%, 11.9%, 21.3% and 39.6% in the GPS-Klo-, BDS-Klo-, BDS-Grid- and GIM-constrained GPS + GLONASS + BDS single-frequency PPP solutions, respectively. Furthermore, the positioning accuracy of the BDS-Grid- and GIM-constrained PPP is generally the same as the ionosphere-free combined single-frequency PPP. Through the combination of GPS, GLONASS and BDS, the positioning accuracy and convergence performance for all single-system single-frequency SPP/PPP solutions can be effectively improved.

Improving GNSS PPP accuracy through WVR PWV augmentation

Using 5 months of observations at a Global Navigation Satellite System (GNSS) and a Water Vapor Radiometer (WVR) collocated station at Tongji University, Shanghai, a mid-latitude coastal city in China with high level of water vapor, we analyzed the precipitable water vapor (PWV) from different sources including WVR, GNSS, Numerical Weather Prediction model (NWP) and radiosonde (RS). The highest correlation coefficient of 99.8% between GNSS PWV and WVR PWV with a linear fitting root-mean-square (RMS) error of 1 mm was obtained. The WVR observations were further applied in GNSS Precise Point Positioning (PPP) to demonstrate its benefits compared to the traditional PPP where troposphere delay was estimated. Both the Global Positioning System (GPS) and Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS) observations were used, and the impact of estimating tropospheric gradients was also investigated. Experiments show that the WVR-constrained PPP improves the weekly repeatability, convergence time, and short-term precision in the vertical component for GPS + GLONASS and GPS-only PPP, in both static and kinematic cases. For the vertical component of daily static GPS + GLONASS PPP, the weekly repeatability of the daily static solutions was improved by ~ 5%; the convergence time was shortened by ~ 30–50%. The short-term static GPS + GLONASS PPP vertical precision was improved by 30–53% when the WVR PWV was used as a constraint and troposphere gradients were estimated. The kinematic GPS-only PPP solution showed 10–15% improvement in the vertical component when the WVR PWV was used as a constraint. However, the kinematic GPS + GLONASS PPP solution showed very limited improvement in the vertical precision when the WVR PWV was constrained. In general, the use of WVR PWV constraint did not improve the horizontal accuracy in either GPS-only or GPS + GLONASS PPP solutions, in either static or kinematic cases.

FCB estimation with three different PPP models: equivalence analysis and experiment tests

Precise and reliable fractional cycle bias (FCB) products are critical for ambiguity resolution of precise point positioning (PPP). Three PPP models are usually adopted to generate the FCB products, i.e., the traditional ionospheric-free combined PPP (IF-PPP) model, the uncombined and unconstrained PPP model (UU-PPP) as well as the ionospheric-constrained PPP (IC-PPP) model. Considering that different observation models and ionospheric delay constraints are used, the applicability and interoperability of the obtained FCB products are assessed. We presented the equivalent conversion formulas of different FCB products obtained with different PPP models, which are then converted and compared. The root mean square (RMS) of the wide-lane (WL) FCB differences for IF-UU, IF-IC and UU-IC is 0.021, 0.024 and 0.010 cycles, while the RMS of the narrow-lane FCB differences is 0.028, 0.018 and 0.021 cycles. The precision of the WL FCBs based on the uncombined PPP models is higher than that based on the IF-PPP model since the new WL ambiguities derived from the uncombined ambiguities are free of the pseudorange noise. The equivalence of the FCB products estimated from the three different PPP models is confirmed in theory and by experiment results. To further evaluate the performance of the three PPP models, the positioning accuracy, the convergence time and the ambiguity fixing success rate are calculated using IGS data. The maximum positioning difference is less than 0.9 mm among the three PPP models. Compared to the float solutions of the IF-PPP, UU-PPP, IC-PPP with GIM model or with re-injected ionospheric delay corrections, the convergence time is shortened by 38.5%, 46.2%, 50.0% and 87.8% and the positioning accuracy improved by 27.1%, 38.9%, 41.1% and 25.7%, respectively. The ambiguity fixing success rate of the uncombined PPP models is slightly higher than that of the combined model, and fast ambiguity-fixed solution can proceed with high-precise ionospheric delay corrections.

Precise point positioning with mixed use of time-differenced and undifferenced carrier phase from multiple GNSS

A multi-GNSS kinematic precise point positioning (PPP) approach that is based on the mixed use of time-differenced and undifferenced carrier phase observations is presented. The approach reduces the number of constant parameters, such as ambiguities and hardware biases, and mitigates quasi-constant systematic errors including residual atmospheric refractions and multipath effects. The effectiveness and efficiency of the proposed approach are validated in some PPP tests of running and vehicle driving. The proposed method requires an accurate initial position. When that is available, up to 71% improvement in positioning accuracy can be achieved compared with traditional PPP. The proposed approach is also computationally efficient, especially for high-rate positioning applications.

Approach for GPS precise time transfer using an augmentation information and zero‐differenced PPP model

This study proposes an approach for global positioning system (GPS) precise time transfer using the augmentation information and zero-differenced precise point positioning (PPP) models. The augmentation information can be real-time generated by constraining the coordinates of the reference stations, it is the difference between the observed distance and the real distance from the satellite to the receiver after considering the modelling errors. As the augmentation information contains the ionosphere delay, troposphere delay, receiver clock, phase ambiguities, ephemeris residuals and the other un-modelling errors, thus some common errors are eliminated and/or reduced after used the augmentation information, then the zero-differenced PPP model can be used for data solution and precise time transfer service. Two pairs of datasets were used to validate the feasibility and effectiveness of the proposed approach. The results show that the accuracy and stability of time transfer are greatly improved by the new approach, especially for the zero baseline. Compared with the traditional PPP time transfer approach, which relies on the precise ephemeris, the new approach used the augmentation correction which contains the ephemeris residuals, thus it can be operated by both precise ephemeris and broadcast ephemeris, and is hence more effective for real-time operation.

Real-Time Precise Point Positioning Using Orbit and Clock Corrections as Quasi-Observations for Improved Detection of Faults

Real-time Precise Point Positioning (PPP) relies on the use of accurate satellite orbit and clock corrections. If these corrections contain large errors or faults, either from the system or by meaconing, they will adversely affect positioning. Therefore, such faults have to be detected and excluded. In traditional PPP, measurements that have faulty corrections are typically excluded as they are merged together. In this contribution, a new PPP model that encompasses the orbit and clock corrections as quasi-observations is presented such that they undergo the fault detection and exclusion process separate from the observations. This enables the use of measurements that have faulty corrections along with predicted values of these corrections in place of the excluded ones. Moreover, the proposed approach allows for inclusion of the complete stochastic information of the corrections. To facilitate modelling of the orbit and clock corrections as quasi-observations, International Global Navigation Satellite System Service (IGS) real-time corrections were characterised over a six-month period. The proposed method is validated and its benefits are demonstrated at two sites using three days of data.