Accuracy Of Precise Point Positioning Research Articles

Double difference method with zero and short base length carrier phase measurements for Navigation with Indian Constellation satellites L5 (1176.45 MHz) signal quality analysis

SummaryThe carrier phase (CP) measurements should be unambiguous to achieve the enhanced accuracy of Global Navigation Satellite System (GNSS) services. However, all the real‐time CP measurements are manipulated by different errors, namely, satellite and receiver clock error, ionosphere delay, troposphere delay, integer ambiguity, etc. Even after removing or minimizing all these errors, the CP measurements are influenced by multipath error and receiver hardware residual or bias. In this research article, a double difference (DD) method is proposed to estimate residual or bias in CP observations of Navigation with Indian Constellation (NavIC). The proposed method abolishes all the common errors and provides bias. However, the CP measurement with a bit of bias value can be considered a high‐quality signal. Here, we investigate the quality of NavIC satellites L5 (1176.45 MHz) signal with real‐time measurements obtained through zero base length (ZBL) and short base length (SBL) experiments conducted at Kurnool (15.79°N, 78.07°E), India. The results show that the CP measurement bias of the L5 signal is within the range ±0.338 and ±1.688 m, respectively, for stationary and moving receivers. The bias was enhanced to 3.71 m for the SBL measurements. The results also demonstrate that the bias is low when carrier to noise (C/No) is high, and its range is nearly the same for all the days. This research would be helpful to estimate the bias that improves accuracy of precise point positioning (PPP) applications.

A Combined Elevation Angle and C/N0 Weighting Method for GNSS PPP on Xiaomi MI8 Smartphones.

Traditionally, an elevation-angle-dependent weighting method is usually used for Global Navigation Satellite System (GNSS) positioning with a geodetic receiver. As smartphones adopt linearly polarized antenna and low-cost GNSS chips, different GNSS observation properties are exhibited. As a result, a carrier-to-noise ratio (C/N0)-dependent weighting method is mostly used for smartphone-based GNSS positioning. However, the C/N0 is subject to the effects of the observation environment, resulting in an unstable observation weight. In this study, we propose a combined elevation angle and C/N0 weighting method for smartphone-based GNSS precise point positioning (PPP) by normalizing the C/N0-derived variances to the scale of the elevation-angle-derived variances. The proposed weighting method is validated in two kinematic PPP tests with different satellite visibility conditions. Compared with the elevation-angle-only and C/N0-only weighting methods, the combined weighting method can effectively enhance the smartphone-based PPP accuracy in a three-dimensional position by 22.7% and 24.2% in an open-sky area, and by 52.0% and 26.0% in a constrained visibility area, respectively.

Multi-GNSS Precise Point Positioning with UWB Tightly Coupled Integration.

Global Navigation Satellite Systems (GNSSs) can provide high-precision positioning services, which can be applied to fields including navigation and positioning, autonomous driving, unmanned aerial vehicles and so on. However, GNSS signals are easily disrupted in complex environments, which results in a positioning performance with a significantly inferior accuracy and lengthier convergence time, particularly for the single GNSS system. In this paper, multi-GNSS precise point positioning (PPP) with tightly integrating ultra-wide band (UWB) technology is presented to implement fast and precise navigation and positioning. The validity of the algorithm is evaluated by a set of GNSS and UWB data. The statistics indicate that multi-GNSS/UWB integration can significantly improve positioning performance in terms of the positioning accuracy and convergence time. The improvement of the positioning performance for the GNSS/UWB tightly coupled integration mainly concerns the north and east directions, and to a lesser extent, the vertical direction. Furthermore, the convergence performance of GNSS/UWB solution is analyzed by simulating GNSS signal interruption. The reliability and robustness of GNSS/UWB solution during GNSS signal interruption is verified. The results show that multi-GNSS/UWB solution can significantly improve the accuracy and convergence speed of PPP.

Integrity monitoring for undifferenced and uncombined PPP under local environmental conditions

Integrity monitoring of precise point positioning (PPP) can provide tightly guaranteed absolute position error bounds for safety-critical applications. However, a complex local environment makes PPP integrity monitoring much more challenging, such as urban canyons. Significant prone multipaths and low observation redundancy are the main difficulties in the accuracy and reliability of PPP. Therefore, we proposed a solution separation-based integrity monitoring algorithm, which is based on a single and dual frequency undifferenced and uncombined PPP model considering compensation for the multipath error distortion by Gaussian overbounding. Both the static and the kinematic data are utilized to test the proposed algorithm. The results show that the proposed algorithm can produce an adequate protection level (PL) in horizontal and vertical directions. Furthermore, the proposed algorithm can obtain a smoother PL and positioning error in a dynamic local environment, and effectively suppress misleading information.

BDS near real-time maneuver detection based on triple-differenced phase observations

The BeiDou Navigation Satellite System (BDS) geostationary earth orbit (GEO) and inclined geosynchronous orbit (IGSO) satellites need frequent orbital maneuvers to keep them in position due to various perturbations. However, common users cannot obtain the exact maneuver times, which may yield a decline in the real-time service performance of the BDS. To solve this problem, we presented a near real-time maneuver detection method for BDS based on triple-differenced phase observations, which can automatically detect the exact start and end times of satellite orbital maneuvers. In this method, the carrier-phase triple-differences residuals are firstly computed using the precise station coordinates, broadcast ephemeris and dual-frequency observations of ground tracking stations. Afterward, the residuals are be modeled using linear regression to identify maneuver times. The observations from the BDS Experimental Tracking Stations (BETS) and the reference time announced by the Beijing Satellite Navigation Center (BSNC) from Day of year (DOY) 100 to DOY 300, 2017 are used to evaluate the performance of the proposed method. The detected maneuver periods are consistent with the announced ones, except the detected start times lag 42 min and end times advance 23 min on average. Then, the detected times are further validated by dynamic precise orbit determination (POD) after the maneuver. The phase residuals and 3D RMS of the orbit differences of maneuvered satellites proved that the accuracy of detected maneuver times is better than 5-minute. At last, the kinematic precise point positioning (PPP) validation is implemented to evaluate the effect of more accurate GEO and IGSO satellites to BDS positioning. Results show that both the convergence and accuracy of BDS PPP are improved by adding one satellite that has ended maneuvering.

A Method to Mitigate the Effects of Strong Geomagnetic Storm on GNSS Precise Point Positioning

AbstractGeomagnetic storm can affect the performance of Global Navigation Satellite System (GNSS) precise positioning services. To mitigate the adverse effects of strong geomagnetic storms, we propose to establish the geometry‐free (GF) cycle slip threshold model based on ionospheric disturbance index rate of total electron content index to reduce the false detection rate of cycle slip in GNSS precise point positioning (PPP) during strong storm periods, thus improving the accuracy and reliability of GNSS PPP. The performance of our proposed model is validated by using 171 International GNSS Service (IGS) tracking stations data on 8 September 2017. The analysis indicates that compared with conventional PPP scheme, the proposed model can improve the positioning accuracy by approximately 14.0% (36.8%) and 23.1% (51.5%) in the horizonal and vertical components for global (high latitudes) stations. Furthermore, the availability of our proposed model is also validated by PPP experiments using 379 IGS tracking stations data during another strong storm occurred on 26 August 2018.

Correction Model of BDS-3 Satellite Pseudorange Multipath Delays and Its Impact on Single-Frequency Precise Point Positioning

Precise point positioning (PPP) is used in many fields. However, pseudorange multipath delay is an important error that restricts its accuracy. Pseudorange multipath delay can be considered as the combination of effective information and observation noise; it can be modeled after removing the observation noise. In this work, elastic nets (EN) regularization denoising method is proposed and compared with L2-norm regularization denoising method. Then, quadratic polynomial (QP) model plus autoregressive (AR) model (QP + AR) are used to model the denoised pseudorange multipath delays. Finally, the modeling results are corrected to the observations to verify the improvement of BDS-3 single-frequency PPP accuracy. Three single-frequency PPP schemes are designed to verify the effectiveness of denoising method and QP + AR model. The experimental results show that the accuracy improvement of B3I and B2a is more obvious than that of B1I and B1C when the modeling values are corrected to the pseudorange observations. The improvement of B3I and B2a in the east (E) and up (U) directions can reach 10.6%∼34.4% and 5.9%∼65.7%, and the improvement of the north (N) direction is mostly less than 10.0%. The accuracy of B1I and B1C in E and U directions can be improved by 0%∼30.7% and 0.4%∼28.6%, respectively, while the accuracy of N direction can be improved slightly or even decreased. Using EN regularization denoising and QP + AR model correction, single-frequency PPP performs better at B3I and B2a, while L2-norm regularization denoising and QP + AR model correction perform better at B1I and B1C. The accuracy improvement of B2a and B3I is more obvious than that of B1I and B1C. The convergence time after MP correction of each frequency is slightly shorter. Overall, the proposed pseudorange multipath delays processing strategy is beneficial in improving the single-frequency PPP of BDS-3 satellite.

Comparison Analysis on the Accuracy of Galileo PPP Using Different Frequency Combinations in Europe

The Galileo constellations are characterized by transmitting GNSS signals on multi-frequencies, which can benefit the robustness and accuracy of the solutions. However, the dual-frequency E1/E5a combinations are generally used for precise point positioning (PPP). In this paper, the performance of Galileo static and kinematic PPP using different dual- and multi-frequency combinations are assessed using observations from the European region. Overall, the accuracy of daily PPP achieved by the dual-frequency GPS, Galileo, and BDS is better than 5 mm in the horizontal direction and better than 10 mm in the vertical direction. Though the number of observed Galileo satellites is less than GPS, the horizontal accuracy can reach 1.6 mm/2.3 mm/5.7 mm on North/East/Up component, which is improved by 59.0% and 12.3% compared to the GPS in the north and up direction. Then, the accuracy of Galileo static PPP is analyzed using different dual- and multi-frequency combinations. Results indicate that the Galileo E1/E5b PPP can degrade the accuracy due to the inter-frequency clock biases between the E1/E5a and E1/E5b combinations. Best accuracy can be achieved for the triple- and four-frequency PPP, which is 4.8 mm in the up direction. The hourly accuracy for the static PPP can reach 5.6 mm/9.2 mm/12.6 mm in the north/east/up direction using the GPS/Galileo/GLONASS/BDS combinations. Finally, a positioning convergence ratio (PCR) indicator, which represents the accuracy of PPP over a period, is used to analyze the convergence time of kinematic PPP. Results indicated that the multi-frequency Galileo observations contribute minorly to the convergence of kinematic PPP. However, Galileo shows the best convergence performance for the single GNSS positioning, and the GPS/Galileo combined PPP achieved the best performance for the PPP using different GNSS combinations.

Estimating the Fractional Cycle Biases for GPS Triple-Frequency Precise Point Positioning with Ambiguity Resolution Based on IGS Ultra-Rapid Predicted Orbits

We investigate the estimation of the fractional cycle biases (FCBs) for GPS triple-frequency uncombined precise point positioning (PPP) with ambiguity resolution (AR) based on the IGS ultra-rapid predicted (IGU) orbits. The impact of the IGU orbit errors on the performance of GPS triple-frequency PPP AR is also assessed. The extra-wide-lane (EWL), wide-lane (WL) and narrow-lane (NL) FCBs are generated with the single difference (SD) between satellites model using the global reference stations based on the IGU orbits. For comparison purposes, the EWL, WL and NL FCBs based on the IGS final precise (IGF) orbits are estimated. Each of the EWL, WL and NL FCBs based on IGF and IGU orbits are converted to the uncombined FCBs to implement the static and kinematic triple-frequency PPP AR. Due to the short wavelengths of NL ambiguities, the IGU orbit errors significantly impact the precision and stability of NL FCBs. An average STD of 0.033 cycles is achieved for the NL FCBs based on IGF orbits, while the value of the NL FCBs based on IGU orbits is 0.133 cycles. In contrast, the EWL and WL FCBs generated based on IGU orbits have comparable precision and stability to those generated based on IGF orbits. The use of IGU orbits results in an increased time-to-first-fix (TTFF) and lower fixing rates compared to the use of IGF orbits. Average TTFFs of 23.3 min (static) and 31.1 min (kinematic) and fixing rates of 98.1% (static) and 97.4% (kinematic) are achieved for the triple-frequency PPP AR based on IGF orbits. The average TTFFs increase to 27.0 min (static) and 37.9 min (kinematic) with fixing rates of 97.0% (static) and 96.3% (kinematic) based on the IGU orbits. The convergence times and positioning accuracy of PPP and PPP AR based on IGU orbits are slightly worse than those based on IGF orbits. Additionally, limited by the number of satellites transmitting three frequency signals, the introduction of the third frequency, L5, has a marginal impact on the performance of PPP and PPP AR. The GPS triple-frequency PPP AR performance is expected to improve with the deployment of new-generation satellites capable of transmitting the L5 signal.

Analysis of dual-frequency solution method for single-frequency precise point positioning based on SEID model for GPS and BDS

The Satellite-specific Epoch-differenced Ionospheric delay (SEID) model can effectively correct ionospheric errors, which is of great significance in the application of entailing low-cost global positioning system (GPS) single-frequency (SF) receivers for retrieving tropospheric delays and deformation monitoring. This study aims to explore the impact of the SEID model on SF and dual-frequency (DF) precise point positioning (PPP) based on the GPS–, BeiDou Navigation Satellite System (BDS) –only and the GPS–BDS dual-system. Two sets of data were collected, corresponding to three test networks with DF stations separated by 34, 139, and 172 km, respectively. The GPS, BDS, and GPS–BDS dual-system observations in the networks were utilized to test positioning results, tropospheric delay and the impact of satellite-induced code bias variations existing in BDS on the positioning of DF PPP with ionosphere-free combinations, ionosphere-constrained SF PPP, and SF PPP based on SEID model transformation (STSF). The results show that the positioning results of STSF PPP became slightly inaccurate with increasing reference station separation distances. However, the SF PPP based on the SEID model exhibited substantially improved positioning accuracy and coordinate repeatability of SF PPP especially with regard to BDS, and obtain similar positioning results of DF PPP. The difference in the Standard Deviation (STD) and Root Mean Square (RMS) of the positioning bias of the GPS-only and GPS-BDS dual systems between DF PPP and STSF PPP was similar within 1 cm, but the difference in the case of BDS was as large as 2 cm in the E and U directions in the networks with separations of 139 and 172 km. Furthermore, the improvement of the STD and RMS of the STSF PPP positioning result was the greatest more than 67% for GPS–, BDS–only, and GPS–BDS dual- system in the networks separated by 34 km compared to SF PPP.

Using only observation station data for PPP ambiguity resolution by UPD estimation

This article proposes a new method for uncalibrated phase delay (UPD) estimation to improve the accuracy of precise point positioning (PPP), which uses only observation station data. This means that the station used to generate the UPDs is the same station to which they are applied. First, dual-frequency observation equations based on a raw PPP model are developed. Then, the UPDs are calculated from integer linear combinations of float ambiguities. Third, with the UPD corrections, the least-squares ambiguity decorrelation adjustment (LAMBDA) method is utilized to obtain the integer ambiguities. Since only observation station data are used for UPD estimation, the partial ambiguity resolution (PAR) method is adopted to increase the possibility of finding a subset of integer ambiguities. The UPD estimation and ambiguity resolution are performed in each epoch. To obtain the correct integer ambiguity, the ratio test and success rate (bootstrapping) are used to evaluate the estimated integer ambiguity. Finally, by treating the integer ambiguities as constants, fixed solutions can be obtained. Quality control is also applied throughout the entire data processing procedure to obtain high quality float and fixed solutions. Data from 22 stations of the International Global Navigation Satellite System (GNSS) Service (IGS) in East Asia on day of year (DOY) 206, 2017, are used to verify the feasibility of this method. The experimental results show that compared with the float solution, the proposed method can significantly improve the accuracy in the east, north and up directions by 24%, 21% and 18% for static PPP and 36%, 18% and 34% for dynamic PPP, respectively. However, the accuracy of the proposed method is still lower than that of the fixed solutions obtained by the PRIDE-PPPAR software, in which the fractional cycle bias is computed based on reference network data. These findings sufficiently show that the proposed method can offer better solution accuracy than the float solution. However, the quality of the UPDs estimated only from observation station data is not as good as that of the estimates obtained based on reference network data.

Assessment and Analysis of the Four-Satellite QZSS Precise Point Positioning and the Integrated Data Processing With GPS

The Quasi-Zenith Satellite System (QZSS), which serves Japan and its surrounding areas, is a regional navigation satellite system developed by Japan Aerospace Exploration Agency. The system is now in a four-satellite constellation with preliminary standalone navigation and positioning capabilities. In this paper, the performance of QZSS-only precise point positioning (PPP) in both static and kinematic modes is initially evaluated using the datasets spanning 11 days from 11 tracking stations in Asia-Pacific regions and the final precise orbit and clock products from the analysis centers GFZ and WUM. For completeness, the GPS/QZSS integrated data processing with GFZ and WUM final products as well as the L6E real-time orbit and clock corrections is also analyzed. The results indicate that the static positioning accuracy of QZSS-only PPP is approximately 4, 2 and 15 cm in the east, north and up directions, respectively, and the static convergence time of QZSS-only PPP with WUM and GFZ products can be 75.2, 44.3 and 45.6 min, and 153.5, 201.6 and 162.8 min in the three directions, respectively. As for the QZSS-only kinematic PPP solutions, the re-convergence repeatedly occurs due to limited available satellites. To achieve more reliable solutions, the inter-system bias parameter in GPS/QZSS PPP processing is recommended to be estimated as random walk process or white noise process. The improvement of post-processed GPS/QZSS PPP over GPS-only case is marginal on position accuracies, but can be several minutes on convergence time. Compared with post-processed GPS/QZSS PPP, the real-time one achieves worse position accuracies but comparable convergence time.

The performance assessment of Precise Point Positioning (PPP) under various observation conditions

Two different methods, absolute and relative positioning, are used in determining point positions with GNSS techniques. Precise Point Positioning (PPP) technique, which is one of the absolute positioning methods, is a powerful position determination method.In this study, the accuracy of PPP has been investigated in terms of session durations, online web services, satellite visibility and urbanization. For this purpose, three of CORS-Tr stations were selected in residential, semi-residential and non-residential areas. Consecutive 31-day data of these stations for the year 2019 were downloaded from server. The 31-day consecutive coordinates were obtained by sending the downloaded RINEX data to AUSPOS. The average of these coordinates was considered as true quantity value. Then, the RINEX data were binned four groups as 1 h, 2 h, 4 h, 6 h. The binned data were evaluated with web-based online PPP services (CSRS-PPP, magicGNSS, APPS) and compared with the true quantity value. In conclusion, it was seen that the best result was obtained in the non-residential area and CSRS-PPP yielded the most accurate results for all session durations.

Study on Multi-GNSS Precise Point Positioning Performance with Adverse Effects of Satellite Signals on Android Smartphone.

The emergence of dual frequency global navigation satellite system (GNSS) chip actively promotes the progress of precise point positioning (PPP) technology in Android smartphones. However, some characteristics of GNSS signals on current smartphones still adversely affect the positioning accuracy of multi-GNSS PPP. In order to reduce the adverse effects on positioning, this paper takes Huawei Mate30 as the experimental object and presents the analysis of multi-GNSS observations from the aspects of carrier-to-noise ratio, cycle slip, gradual accumulation of phase error, and pseudorange residual. Accordingly, we establish a multi-GNSS PPP mathematical model that is more suitable for GNSS observations from a smartphone. The stochastic model is composed of GNSS step function variances depending on carrier-to-noise ratio, and the robust Kalman filter is applied to parameter estimation. The multi-GNSS experimental results show that the proposed PPP method can significantly reduce the effect of poor satellite signal quality on positioning accuracy. Compared with the conventional PPP model, the root mean square (RMS) of GPS/BeiDou (BDS)/GLONASS static PPP horizontal and vertical errors in the initial 10 min decreased by 23.71% and 62.06%, respectively, and the horizontal positioning accuracy reached 10 cm within 100 min. Meanwhile, the kinematic PPP maximum three-dimensional positioning error of GPS/BDS/GLONASS decreased from 16.543 to 10.317 m.

The Impact of Different Mapping Function Models and Meteorological Parameter Calculation Methods on the Calculation Results of Single-Frequency Precise Point Positioning with Increased Tropospheric Gradient

Tropospheric delay is one of the main errors in precise point positioning (PPP). The inaccuracy of the tropospheric delay model will inevitably lead to a decrease in PPP accuracy. Therefore, the influence of the tropospheric gradient on the positioning accuracy should be considered in the processing of tropospheric delay. At the same time, the effects of different mapping function models and meteorological parameter calculation methods on the tropospheric delay accuracy of single-frequency PPP (SF PPP) are analyzed. Twelve MGEX stations, which are evenly distributed in the world, are used in this article. Taking into account the seasonal variation of the tropospheric delay, the observation times adopted are 2016, 2017, and 2018 for different seasons (winter, day of year (DOY): 22–28; spring, DOY: 92–98; summer, DOY: 199–205; and autumn, DOY: 275–281). Then, according to different mapping function models and meteorological parameter calculation methods, a total of 7056 tests and 9072 tests are performed, respectively. The following results were obtained after comparative analysis. (1) When the same method is used for calculating meteorological parameters, the percentage with improved tropospheric delay repeatability calculated by the Hopfield mapping function model (MFM3) is the highest, reaching more than 70%, and by Vienna Mapping Functions 3 (VMF3, grid resolution is 1°), the mapping function model (MFM8) is the lowest, less than 67.5%. The percentage with improved position repeatability is highest in the north (N) direction and lowest in the up (U) direction. (2) Using the same mapping function model, the correction of the tropospheric gradient model has a greater impact on calculating the repeatability percentage of the tropospheric delay and the position. Compared with standard atmospheric parameters, other calculation methods of meteorological parameters have little effect on the percentage increase of the tropospheric delay value and the positioning result after adding the tropospheric gradient model. It shows that different calculation methods of meteorological parameters have little effect on the calculation of tropospheric delay and position, different mapping function models have a large effect on the calculation of tropospheric delay and position, and the tropospheric gradient model has the greatest influence on the calculation of tropospheric delay and position.

Performance assessment of real-time multi-GNSS integrated PPP with uncombined and ionospheric-free combined observables

For precise position services, the real-time precise point positioning (PPP) is a promising technology. The real-time PPP performance is expected to be improved by multi-system combination. The performance of real-time multi-system PPP needs to be periodically investigated, with the increasing number of available satellites and the continuously improved quality of real-time precise products of satellite clocks and orbits. In this study, a comprehensive performance assessment is conducted for the four-system integrated real-time PPP (FSIRT-PPP) with GPS, BDS, Galileo and GLONASS in both static and kinematic modes. The datasets from 118 stations spanning approximately a month are used for analysis, and the real-time stream CLK93 is employed. The superior performance of FSIRT-PPP is validated by comparing with the results of GPS/BDS, GPS/Galileo, GPS/GLONASS, GPS-only, BDS-only, Galileo-only and GLONASS-only cases. The FSIRT-PPP using ionospheric-free (IF) combined observables can achieve a convergence time of 10.9, 4.8 and 11.8 min and a positioning accuracy of 0.4, 0.5 and 0.7 cm in the static mode in the east, north and up directions, respectively, while the derived statistic is 15.4, 7.0 and 16.4 min, and 1.6, 1.2 and 3.4 cm in the kinematic mode in the three directions, respectively. Moreover, we also compare the position solutions of real-time PPP adopting IF combined and uncombined (UC) observables, and prove the mathematical equivalence between the two PPP models in the converged stage, provided that there are no external ionospheric corrections or constraints given to the estimated ionospheric delays in the UC model. The difference between the fully converged positioning accuracy of IF-based and UC-based real-time PPP is marginal, but the UC-based real-time PPP has longer convergence time due to the influence of the significant unmodeled time-varying errors in the real-time precise products as well as the different parameterization between them. For completeness, the real-time kinematic PPP results in harsh environments and the post-processed PPP results are also presented.

Effectiveness of L1-norm regularization sidereal filtering for precise point positioning

Integer ambiguity resolution is critical for achieving positions of high precision and reliability of precise point positioning (PPP). However, as an important error source in global navigation satellite system (GNSS), multipath interference limits the ability of PPP in high-accuracy GNSS positioning applications. Thus, to guarantee the performance of PPP ambiguity resolution techniques in a multipath environment, a sidereal filtering technique based on sparsity promoting regularization is adopted to mitigate the multipath error. The key idea of the proposed strategy emphasizes the use of the L1 norm to extract multipath from noisy carrier phase residuals. The classical single-difference between-satellites method is used to fix PPP with the estimated phase clocks/bias products for obtaining carrier phase residuals in the previous period. Two GPS datasets are adopted to assess the denoising effect of the multipath model and the performance of the proposed strategy. The carrier phase residuals of static PPP ambiguity resolution and the positioning accuracy of kinematic float PPP after the application of the multipath model are used to reflect the final filtering performance. Results show that the multipath model based on first-order regularization can improve the RMS of carrier phase residuals by approximately 49.8% compared with the solution without multipath mitigation. In kinematic float PPP, a mean coordinate improvement of 49.7% for day of year (DOY) 273 and 57.8% for DOY 275 in 2017 could be achieved.

Assessing the Positioning Performance Under the Effects of Strong Ionospheric Anomalies With Multi‐GNSS in Hong Kong

AbstractGlobal navigation satellite system (GNSS) precise positioning performance will be strongly affected under severe ionospheric anomaly conditions. The combination of multi‐GNSS can increase the available observations and improve the geometry of continuously tracked satellites. This paper focuses on assessing the positioning performance with the combination of Global Positioning System (GPS), Global'naya Navigatsionnaya Sputnikova Sistema (GLONASS), and BeiDou System (BDS) around the St. Patrick's Day geomagnetic storm (9–18 March) in 2015 in Hong Kong. The rate of total electron content (TEC) index (ROTI) indicates severe ionospheric anomalies before the superstorm, while it was absent during the main phase of the storm in Hong Kong. Furthermore, strong scintillation events on signal‐to‐noise ratio (SNR) and multipath (MP) observables are observed during ionospheric anomalies period. Then the performance of single‐point positioning (SPP) and precise point positioning (PPP) with multi‐GNSS is shown. The ionospheric scintillation events may reduce pseudorange accuracy but affect SPP performance a little in this study, while the PPP accuracy is vastly decreased due to the subsequent reconvergence caused by frequent cycle slip (CS). Compared to PPP solutions with GPS only, the accuracy is improved significantly with the combination of multi‐GNSS.

Assessment of the Accuracy and Convergence Period of Precise Point Positioning

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Multi-constellation GNSS precise point positioning with multi-frequency raw observations and dual-frequency observations of ionospheric-free linear combination

Precise point positioning (PPP) is famous for its capability of high-precision positioning with just one station as long as the receiver can receive global navigation satellite system (GNSS) signals. With the rapid development of BDS and Galileo, the number of available satellites for positioning has increased significantly. In addition, GPS III, GLONASS-K, BDS, and Galileo satellites can transmit triple-frequency signals. The potentials of multi-constellation GNSS PPP requires further analysis on a global scale. Therefore, we selected 96 multi-GNSS experiment (MGEX) stations with a global distribution and used 1 week’s data to assess the PPP performance. The results show that the PPP based on multi-frequency raw observations with spatial and temporal constraints has better performance than PPP using dual-frequency ionospheric-free observations. The main contribution of multi-constellation GNSS PPP is to shorten the convergence time. The convergence time for GPS PPP is approximately 40 min, which can be shortened to less than 20 min in multi-GNSS PPP. After convergence, the positioning accuracy of multi-GNSS PPP is improved by 0.5 to 1.0 cm compared with GPS or GLONASS PPP. The positioning accuracy of multi-GNSS could be further improved in the future with the BDS and Galileo precise products of orbits, clock and phase center offset/variation.